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Cet article propose un nouveau concept de parc industriel à valeur partagée basé sur la collaboration entre plusieurs intervenants, orienté vers l’innovation marché et visant la création de bénéfices sociaux. Il expose le résultat d’une première étape reliée à une méthodologie de recherche basée sur la conception comprenant une revue de la littérature décrivant divers types de parcs existants et s’adaptant au contexte de l’industrie forestière Canadienne. L’idée du Shared Value Park représente une solution répondant aux enjeux du développement durable et à la conjoncture actuelle des marchés des produits du bois en permettant aux entreprises impliquées de transformer leur modèle d’affaires et en facilitant la mise en place de stratégies de diversification. Le type de collaboration retrouvée sur le parc accéléra le développement de bioproduits, issus de la biomasse forestière, tout en permettant de résoudre les défis d’investissement, d’innovations et de développement des marchés visés. La structure du parc proposé permet la création de prospérité, d’avantage concurrentiel durable et la croissance économique recherchés. Bien qu’aucune étude de cas n’ait encore été complétée, une discussion concernant des avenues de recherches se rapportant aux outils à développer permettant de le faire termine le document, This article proposes a new concept of industrial park creating shared value based on collaboration between several stakeholders, market-oriented innovation and aiming at social benefits creation. It exposes the result of the first step of a design-based research methodology consisting in a literature review describing various types of existing parks and taking the context of the Canadian forest industry into account. The concept of Shared Value Park is a solution to meet the challenges of sustainable development and the current conditions in the forest products markets by allowing companies involved to transform their business models and facilitate the implementation of diversification strategies. The type of collaboration found in the park will speed up the development of bioproducts, from forest biomass, and help solve challenges, involving investment, innovation and markets development while creating the expected prosperity, sustainable competitive advantage for involved firms, and economic growth. While no case study has been completed on shared value parks, a discussion about research avenues related to enabling shared value parks concludes the paper

This paper proposes a method to restructure the forest value chain using intermediaries when a wider range of forest values should be managed for several stakeholders. This method leads to the definition of the strategic vision of the intermediary, including its value proposition and its required competencies, assuming that actors in the value chain are prepared to revise their business approach to enable effective collaboration and knowledge sharing. The method is used to support management of public forests in the Province of Quebec, in Eastern Canada. Basically, the intermediary, referred to as the integrator-supplier (IS) in the application case, enables several stakeholders, including the government, the forest industry, regional authorities, recreation organizations, and First Nations, to cnmmunicate, to set compatible goals, and to synchronize their activities. These activities and interactions must all be effectively carried out to maximize the overall benefits of forest management. Three critical issues for successful development of the IS are identified. The results present functional descriptions of seven development scenarios for effective use of intermediation in forest value chains.

Forest products value chains (FPVC) are complex networks of units incorporating different goals and beliefs. These units need to work toCJ gether to generate the different elements of value. To study these value chains, a common representation and understanding of the different components of a value chain must be obtained. This will permit the evaluation of forest and industry strategies, supply chain configurations, and planning approaches using simulations. Agent-based modelling (ABM) is favoured to facilitate the assessment of different scenarios; however, information and knowledge sharing (IKS) in a collaborative modelling context remains an issue. This paper discusses the need for collaborative modelling and simulation of the FPVC and surveys the literature about the most significant standardization initiatives for IKS and ABM platforms, with focus on the FPVC. Then the key findings are explained, and a road map leading to defining a standard for value chain modelling is proposed.

This article presents rolling horizon simulation models and performance analysis of partially and fully integrated sales and operations planning (S&OP) against traditional decoupled planning in a multi-site make-to-order (MTO) based manufacturing supply chain. Three simulation models are developed illustrating, respectively, the fully integrated S&OP model, which integrates cross-functional planning of sales, production, distribution, and procurement centrally; the partially integrated S&OP model, in which the joint sales and production planning is performed centrally while distribution and procurement are planned separately at each site; and the decoupled planning model, in which sales planning is carried out centrally while production, distribution, and procurement are planned separately and locally. A solution procedure is provided for each model so that a more realistic planning process can be simulated. Performances of rolling horizon simulation models are evaluated against those of the fixed horizon deterministic models. The results demonstrate that while deterministic models are important for theoretical studies, they are insufficient for decision support and performance evaluations in a real business environment. A rolling horizon simulation model is required to provide more realistic solutions. The effects of demand uncertainties and forecast inaccuracies are incorporated in the evaluation. The study is carried out based on a real industrial case of a Canadian-based oriented strand board (OSB) manufacturing company.

The research leading to the modeling framework presented in this paper was motivated by the need to provide Canadian pulp and paper producers with a means of maximizing the value created from available fibre supplies. The proposed approach involves finding optimal strategies for partitioning fibre supplies into grades, allocating fibre grades to process streams, selecting appropriate production technologies and capacities, and establishing end-product range compositions and production volumes. These strategies are elaborated with a mixed-integer programming model which can be solved using commercial optimization software. Three test case scenarios are used to validate the model and illustrate how it can be applied to strategic and tactical decision making. A variant of this model has also been applied to an industrial planning problem.

There is an extensive amount of research literature about the concept of agility, describing its drivers and capabilities, and even suggesting methodologies to develop agility. However, most of these efforts remain vague with respect to the characteristics and the expected contributions of the technologies involved or required. This paper proposes an agility reference model; a unifying conceptual representation of agility in terms of the necessary capabilities needed by every process involved in the enterprise seeking for agility. Agility is described using three capabilities which are believed to be the sources of competitive advantages; flexibility, responsiveness, and autonomy. It is shown that each capability addresses some specific issues and can only be thoroughly developed if the technologies used are characterized with some specific attributes or properties. The idea behind the proposed agility reference model was to derive a typology framework that emphasizes the taxonomy of the market interaction strategies for furniture products, and the competitive priorities that should be targeted by furniture enterprises aiming to be agile. Accordingly, the issues related to the different agility capabilities were discussed in the context of the furniture enterprise of the future. Then, the suitability of the proposed model for the derivation of the typology was explored based on case studies on two furniture manufacturing enterprises. The case studies analyze the context in terms of competitive priorities and customization strategies and investigate the agility properties of the technologies in use.

This paper is based on wood supply chain (WSC) data collected in six countries (Canada, Chile, France, Poland, Sweden, and USA) where a total of 94 local actors and experts were consulted. For each WSC studied, processes for operational plan-ning and execution of the procurement activities were mapped. Descriptions of the information, material and financial flows were also completed. Three basic designs of planning systems were identified, and for each design, a decision matrix was de-vised. WSC agility capabilities were assessed according to a four dimensions refer-ence model and compared with those theoretically required by the environment's uncertainties. When comparing location of the decoupling point, agility capabilities, and average order fulfilment cycle time of each WSC, it was possible to reinforce results found in the literature which state that supply chain agility is linked to shorter order fulfilment cycle time. Finally, the personalisation capabilities of each WSC were assessed and two key processes were identified where most of the product differen-tiation activities along a WSC occur.

Recent economic and international threats to western industries have encouraged companies to increase their performance in all ways possible. Many look to deal quickly with disturbances, reduce inventory, and exchange information promptly throughout the supply chain. In other words they want to become more agile. To reach this objective it is critical for planning systems to present planning strategies adapted to the different contexts, to attain better performances. Due to consolidation, the development of integrated supply chains and the use of inter-organizational information systems have increased business interdependencies and in turn the need for increased collaboration to deal with disturbance in a synchronized way. Thus, agility and synchronization in supply chains are critical to maintain overall performance. In order to develop tools to increase the agility of the supply chain and to promote the collaborative management of such disturbances, agent-based technology takes advantage of the ability of agents to make autonomous decisions in a distributed network through the use of advanced collaboration mechanisms. Moreover, because of the highly instable and dynamic environment of today's supply chains, planning agents must handle multiple problem solving approaches. This paper proposes a Multi-behavior planning agent model using different planning strategies when decisions are supported by a distributed planning system. The implementation of this solution is realized through the FOR@C experimental agent-based platform, dedicated to supply chain planning for the lumber industry.

The agent paradigm is widely used to create supply chain simulation tools. Despite its attractiveness and extensive utilization in research, agent technology and its integration with distributed supply chain planning tools still represent an open field. In particular, there is a vacuum of research in the analysis phase of agent-based methodological frameworks. This phase represents the early modeling effort, considerably influencing the whole creation process and the resulting experiments. To contribute to fill this research gap, this paper presents a methodological framework called FAMASS (FORAC Architecture for Modeling Agent-based Simulation for Supply chain planning). It aims to provide a uniform representation of distributed Advanced Planning and Scheduling (d-APS) systems nsing agent technology to support simulation analysts. It aims to guide them in defining what are the functional requirements of possible simulation scenarios, as well as their related experimental definitions. It also guides the analysts to deploy the resulting analysis models into specification and design models. The FAMASS was tested through a proof-of-concept case in the forest products indnstry.

Considering the effects of globalisation, the increase of production and energy costs, and the introduction of advanced technologies, companies need to change their way of doing business if they want to stay competitive. One way of doing this is to establish collaborations with suppliers, distributors and retailers, in order to exchange products efficiently and create value for customers. Nevertheless, the structure of the collaboration must be designed carefully and some coordination mechanisms must be implemented to support this way of doing business. In this article, we first analyse: why companies work together, how they should build their partnership, and which strategies they can implement to facilitate coordination of supply chain activities. We then report a case study of collaboration in the forest industry that shows the benefits of implementing coordination mechanisms as well as the necessity of using incentives to better share these benefits

Forestry has contributed many problems to the Operations Research (OR) community. At the same time, OR has developed many models and solution methods for use in forestry. In this article, we describe the current status of research on the application of OR methods to forestry and a number of research challenges or open questions that we believe will be of interest to both researchers and practitioners. The areas covered include strategic, tactical and operational planning, fire management, conservation and the use of OR to address environmental concerns. The paper also considers more general methodological areas that are important to forestry including uncertainty, multiple objectives and hierarchical planning.

A supply chain is the set of companies producing or carrying products to customers. In such a supply chain, the bullwhip effect is the amplification of demand variability that is distortion in information when this information travels from one end of a supply chain to the order. Inefficiencies which are due to this effect are excessive inventory poor customer service ineffective transportations, missed production schedules…. A game called the Beer Game is a widely used classroom exercise for demonstrating the dynamics in a supply chain. We focus on an adaptation of this game to the forest industry : the Québec Wood Supply Game. We has simulated this game in a spredsheet program : this first implementation is the base of the multi-agent simulation presented in this paper where intelligent agents represent companies. These agents will simulate how comapanies order, produce and store products. In this paper. We describe the supply chain model in the Quebec Wood Supply Game and how we will make it more realistic with agents. However, we present neither our spreadsheet simulation of this game nor our solution to the bullwhip effect

This paper explores past and current developments and applications of decision theaters and discusses their potential benefits for participatory planning in the forest sector in Québec. A participatory mechanism involving the users of forest resources and the territory is illustrated through three regional cases studies. We identify the main challenges and discuss how decision theaters can contribute in addressing them. The next steps of our research are finally presented.

Recent economic and international threats to occidental industries have encouraged companies to rethink their planning systems. Due to consolidation, the development of integrated supply chains and the use of inter-organizational information systems have increased business interdependencies and the need for collaboration. Thus, agility and the ability to deal quickly with disturbances in supply chains are critical to maintain overall performance. In order to develop tools to increase the agility of the supply chain and to promote the collaborative management of such disturbances, agent-based technology takes advantage of the ability of agents to make autonomous decisions in a distributed network. This paper proposes a multi-behavior agent model using different decision making approaches in a context where planning decisions are supported by a distributed advanced planning system (d-APS). The implementation of this solution is realized through the FOR@C experimental agent-based platform, dedicated to the supply chain planning for the forest products industry.

Recent developments in supply chain planning have emerged from the field of agent technology and distributed decision making. Although several attempts have been made to exploit agent technology to design supply chain simulation tools, the integration of simulation with distributed supply chain planning tools is still a challenge. This paper aims at investigating this aspect of supply chain planning simulation through the use of theoretical contributions found in the field of simulation, systems theory, distributed decision making and agent-based software engineering. More specifically, this paper first proposes a conceptual framework for modeling “distributed agent-based Advanced Planning and Scheduling” (d-APS). Next, derived from this framework, it proposes some specific methods for understanding and modeling simulation problems at the initial phase of the modeling effort. This early phase is critical because it considerably influences the whole development process and the resulting simulation environment, but it is usually neglected in the concerned literature. Finally, a theoretical illustrative case is presented in the lumber supply chain.

In today's industrial context, competitiveness is closely associated with supply chain performance. The ongoing development of integrated supply chains has increased the importance of supply chain management. This paper focuses on the design of coordination mechanisms that determine how partners interact to coordinate their production planning. We present a simulation tool to aid in the design of coordination mechanisms using multi-behaviour agents in an agent-based planning system where agents act as partners. The implementation of this solution is realised through the FORAC agent-based planning platform, which is dedicated to supply chain production planning and simulation for the lumber industry.

Agent-based systems have been employed in the Supply Chain Management field since the 1990s. In spite of its appealing and extensive use in both research and practice, the agent technology and its integration with advanced supply chain planning and scheduling tools still represent an emergent field with many open research questions. Particularly, the literature fails to provide an integrated framework to identify, model and conduct simulation experiments covering the whole simulation cycle. Indeed, the initial modelling effort performed at the analysis phase is especially neglected by the literature concerned. This early phase is critical because it considerably influences the whole development process as well as the resulting simulation experiments. Thus, this article presents a novel methodological framework called FAMASS (FORAC Architecture for Modelling Agent-based Simulation for Supply chain planning), which provides: (i) a uniform representation of distributed advanced supply chain planning and scheduling systems using agent technology; and (ii) a methodological approach supporting analysts in defining functional requirements of possible simulation experiments. The proposed methodological framework was tested through a real-scale proof-of-concept case employing data from two industrial partners.

This paper addresses the problem of planning and scheduling operations when processing a multiproduct order in a Symbiotic Manufacturing Network (SMN). The order is characterized for each of its products, by linear routings of operations which can be performed in parallel by different contracting firms of the network. We first present a characterization of the decision process for planning and scheduling operations in SMN. Next, we propose a bidding scheme expressing pricetime trade-off and a multi-commodity network model that can be used to plan and schedule many types of order-based customized production. Finally, an illustrative example is detailed to permit full comprehension of the approach.

This paper presents a simple yet effective approach for unquality-costing in an outsourcing/subcontracting environment. It first presents some of the usual approaches for defining supply relations based on cost-quality issues and then introduces our proposed unquality-costing sampling plans by variables. The approach is derived from the Taguchi loss-function model. A simple sampling Table is presented for the case of symmetric quadratic loss-functions and an illustrative example of its application in a practical setting is then presented. The last Section of the paper finally discusses the advantages and disadvantages resulting from its generalized application to outsourcing and subcontracting within a network manufacturing environment.

This article deals with problems related to the integration of reverse logistics activities within an organization and to the coordination of this new system. Reverse logistics activities refer to the recovery and processing of unused products and to the redistribution of reusable materials. For better control and management of these activities, new approaches and information support system are proposed here. A new organizational system, which represents the course of the operational processes and the management of the organization’s resources (labor, material, etc.), and an information system architecture are proposed for a rehabilitation center.

The classic wood supply optimisation model maximises even-flow harvest levels and implicitly assumes infinite fibre demand. In many jurisdictions, this modelling assumption is a poor fit for actual fibre consumption, which is typically a subset of total fibre allocation. Failure of the model to anticipate this bias in industrial wood fibre consumption has been linked to increased risk of wood supply failure. In particular, we examine the distributed wood supply planning problem where the roles of forest owner and fibre consumer are played by independent agents. We use game theory to frame interactions between public forest land managers and industrial fibre consumers. We show that the distributed wood supply planning problem can be modelled more accurately using a bi-level formulation and present an extension of the classic wood supply optimisation model that explicitly anticipates industrial fibre consumption behaviour. We present a solution methodology that can solve a convex special case of the problem to global optimality and compare output and solution times of classic and bi-level model formulations using a computational experiment on a realistic dataset. Experimental results show that the bi-level formulation can mitigate risk of wood supply failure., La formulation classique du modèle d’optimisation de la possibilité forestière maximise le rendement soutenu et pose l’hypothèse implicite que la demande de fibre est infinie. Dans plusieurs juridictions, cette hypothèse représente mal la réelle consommation de fibre qui est typiquement un sous-ensemble de l’attribution totale. L’incapacité du modèle classique de prévoir l’effet de ce biais entre la possibilité forestière et la consommation réelle est liée a` une hausse du risque de ruptures de stock. En particulier, nous examinons le problème de planification distribuée de l’approvisionnement en bois où des agents indépendants jouent les rôles de propriétaire de la ressource forestière et de consommateur de la fibre. Nous utilisons la théorie du jeu pour encadrer les interactions entre le gestionnaire de la ressource et le consommateur industriel. Nous démontrons que le problème de planification distribuée de l’approvisionnement en bois peut être modélisé plus justement avec une formulation biniveau, et nous présentons une extension du modèle d’optimisation classique pouvant anticiper le comportement du consommateur de fibre industriel. Nous présentons une méthodologie pour résoudre un cas spécial convexe a` l’optimalité globale, et nous comparons les performances expérimentales des formulations classiques et biniveaux a` l’aide d’un jeu de données synthétique réaliste. Les résultats expérimentaux montrent que le modèle biniveau peux atténuer le risque de ruptures de stock.

To overcome declining markets and low-cost competition, Canadian pulp and paper (P&P) mills are considering the diversification of their product platform. Investing in bioenergy is emerging as a promising way to boost the sector. In this paper, we present a mathematical programming approach to evaluate the profitability of bioenergy investments in the case of a P&P mill, while assessing technical and associated economic risks. The mill, called the integrated forest biorefinery (IFBR), could produce a set of high-value bioproducts from biomass generated in the mill or supplied from outside. P&P activity generates residues, such as black liquor and pulp sludge, which could be used to produce bioenergy. P&P activity should then be well managed, by considering the possibility of temporarily stopping the production of P&P, while assuming the costs associated with the shutdowns. The objective is to develop a mathematically-based approach for investors and stakeholders, within the forest sector that aims to optimise the value creation network of the IFBR and to maximise the profitability of future investments in bioenergy, while optimising the existing P&P activity.

The pulp and paper industry depends on a long and integrated supply chain. Forest products start in forest harvest areas as trees and end up as multiple products used in the dayto-day life of all people. The lead time from the first step to the last is long and involves many steps operated by several companies and organizations. In this overview paper we describe the supply chain in its entirety, its participants and the planning problems arising along the chain. We divide the planning problems into strategic, tactical and operative in a supply chain matrix, describe their characteristics and provide applications as illustrations. We discuss the need for information and decision support for planners in each of these areas. This relates to planning within a single company as well as integrated planning across several. A number of tailor-made systems have been developed and published in the literature and we describe these tools/systems together with their characteristics and results. We conclude with a discussion of current issues and outline future research areas.

In the province of Québec, the government provides 25% of the volume of timber that is annually cut in crown forests through sealed-bid one-winner auctions. It was noted that many offers are made for some areas but few or none are made for many other areas. As such, a significant number of the timber volumes remains unsold. However, the combination of areas to form bundles can provide economy of scale that is not seen otherwise. We highlight some issues regarding the current allocation system and we analyse the effectiveness of different bundling systems in maximizing government revenues and enhancing bidders' competitiveness. We use actual forest data to evaluate different rules and strategies for the creation and allocation of partial and full bundles. Our results suggest that the use of the option of bundling forests areas makes the auction process more beneficial to the majority of stakeholders: Government revenues are increased; the bidding companies are more likely to obtain the desired volumes and pay less for harvesting and equipment relocation; and greenhouse gas emissions are reduced.

Les nouvelles technologies, la mondialisation et l'exigence accrue des consommateurs forcent les entreprises à revoir leurs modèles et leurs processus d'affaires dans le but de maintenir leur différenciation et leur compétitivité. De plus en plus d'entreprises tentent d'établir des relations privilégiées avec leurs fournisseurs et/ou leurs distributeurs de façon à maximiser leur synergie, à échanger des services et à partager les risques. Dans notre étude, nous nous sommes intéressés aux relations de collaboration interentreprises et plus particulièrement au cas d'un partenariat entre un distributeur et un manufacturier oeuvrant dans le secteur agroalimentaire. Nous avons proposé une méthodologie supportant la mise en œuvre d'une collaboration efficace. Celle-ci est notamment inspire des pratiques du CPFR (Collaborative planning, forecasting and replenishment). De notre étude, nous avons conclu que l'implantation de processus interentreprises supportant la gestion des prix, des promotions et des inventaires était essentielle à l'établissement d'une relation de confiance et au développement des affaires. De plus, la compatibilité technologique s'avère fondamentale pour accélérer les échanges d'information et les processus interentreprises.

Most research regarding revenue management in manufacturing has considered only a short-term planning horizon, assuming supply and production data exogenously given. Motivated by the case of the Canadian softwood lumber industry, this paper offers additionally a medium-term visibility for firms with limited capacity and faced with seasonal markets. We propose a demand management process for Make-To-Stock environments, integrating sales and operations planning (S&OP) and order promising based on revenue management concepts. Given heterogeneous customers, divergent product structure and multiple sourcing locations in a multi-period context, we first define a multi-level decision framework in order to support medium-term, short-term and real-time sales decisions in a way to maximize profits and to enhance the service level offered to high-priority customers. We further propose a mathematical formulation integrating an S&OP network model in the Canadian softwood lumber industry and an order promising model using nested booking limits. This new formulation allows reviewing previous order promising decisions while respecting sales commitments. A rolling horizon simulation is used to evaluate the performance of the proposed process in various demand scenarios and provides evidence that better performances can be achieved compared to common demand management practices by integrating S&OP and revenue management concepts.

A game called the Quebec Wood Supply Game (QWSG) is a role-playing simulation based on the Beer Game for teaching Supply Chain (SC) dynamics, and, in particular, the bullwhip effect. In this context, this paper describes and compares two simulators based on the QWSG which may be used to study decision making and its impact on SC dynamics. We first focus on the direct implementation of the QWSG in a spreadsheet program. This spreadsheet model is the base on which we next build a more complex MultiAgent Based Simulation (MABS) in which JACK™ agents represent companies. Finally, we compare the respective advantages of each simulator. We identify the features of a SC model making a spreadsheet simulation impossible, and those for which a spreadsheet simulation is better, as good as, or worse than MABS.

Purpose: The objective of this paper is to provide a systematic literature review of recent developments in methodological frameworks for the modelling and simulation of agent-based advanced supply chain planning systems. Design/methodology/approach: A systematic literature review is provided to identify, select and make an analysis and a critical summary of all suitable studies in the area. It is organized into two blocks: the first one covers agent-based supply chain planning systems in general terms, while the second one specializes the previous search to identify those works explicitly containing methodological aspects. Findings: Among sixty suitable manuscripts identified in the primary literature search, only seven explicitly considered the methodological aspects. In addition, we noted that, in general, the notion of advanced supply chain planning is not considered unambiguously, that the social and individual aspects of the agent society are not taken into account in a clear manner in several studies and that a significant part of the works are of a theoretical nature, with few real-scale industrial applications. An integrated framework covering all phases of the modelling and simulation process is still lacking in the literature visited. Research limitations/implications: The main research limitations are related to the period covered (last four years), the selected scientific databases, the selected language (i.e. English) and the use of only one assessment framework for the descriptive evaluation part. Practical implications: The identification of recent works in the domain and discussion concerning their limitations can help pave the way for new and innovative researches towards a complete methodological framework for agent-based advanced supply chain planning systems. Originality/value: As there are no recent state-of-the-art reviews in the domain of methodological frameworks for agent-based supply chain planning, this paper contributes to systematizing

This paper examines the flow synchronization problem between a manufacturing location and multiple destinations. Multiple products can be shipped from the manufacturing location to different locations via multiple transportation modes. These transportation modes may have different transportation lead times. The transportation costs structure of the different transportation modes offer economies of scale and can be represented by general piecewise linear functions. The production system at the manufacturing location is a serial process with a bottleneck stage. At the bottleneck stage, a predetermined production sequence must be maintained as is the case in some process-based industries. We propose a tight mixed integer programming model for integrated planning of production and distribution in the network. We show that by adding simple valid inequalities and special 0-1 variables, major computational improvements can be achieved when solving this problem with commercial solvers such as Cplex. We also propose a sequential solution approach, based on the independent, but synchronized, solutions of the production and distribution sub-problems. Finally, the solution methods proposed are tested experimentally for realistic problems and the advantage of integrated planning over independent but synchronized planning is assessed.

Objective: This paper aims to develop a basic understanding of a demand management process integrating sales and operations planning (S&OP) and order promising in a Make-To-Stock environment and to compare different demand management policies. Contribution: Typical researches about demand management processes analyze few system specifications or vary few potential factors one at time. Yet, we can get additional insights by employing design of experiments (DOE). Methodology: For making promises, we compare a First-Come First-Served approach to an approach using nested booking limits and giving advantage to profitable customers and attractive periods. Considering various sequences of order arrival, we generate Kriging metamodels that best describe the nonlinear relationships between the simulation responses and system factors for Canadian softwood lumber firms. We employ a Latin hypercube design to take into account different environmental scenarios. Results: Our analysis reveals the potential to improve the performance of the demand management process if we know high-priority customers needs before fulfilling less-priority orders and if we use nested booking limits concept.

Shermag Inc. is a vertically integrated furniture company with business units across the supply chain from the forest to the final customer. During the last decade, Shermag has been losing market share to low-cost Asian manufacturers. To reduce the procurement and other significant costs of Shermag's raw material (wood), which constitute a major component of its total furniture cost, we developed a tool to optimize the tactical planning of the company's wood supply chain. We propose an optimization-based approach for coordinating operations at each echelon of the wood supply chain. However, the problem size caused computer-related issues, such as long processing times and computer crashes. In our proposed solution approach, we use decomposition to overcome these issues. Our implementation uses C++, CPLEX (optimization software), and Microsoft Access. In this paper, we present a comparative study of traditional decision making versus optimal decision making. Using Shermag data for 2004 and 2005, we show that our solution reduces total operations costs by more than 22 percent. For any set of parameters, the tool can generate a good, feasible solution. These results convinced Shermag to use our tool for future configurations of its supply chain network.

One of the important objectives of supply chain S&OP (Sales and Operations Planning) is the profitable alignment of customer demand with supply chain capabilities through the coordinated planning of sales, production, distribution, and procurement. In the make-to-order manufacturing context considered in this paper, sales plans cover both contract and spot sales, and procurement plans require the selection of supplier contracts. S&OP decisions also involve the allocation of capacity to support sales plans. This article studies the coordinated contract selection and capacity allocation problem, in a three-tier manufacturing supply chain, with the objective to maximize the manufacturer's profitability. Using a modeling approach based on stochastic programming with recourse, we show how these S&OP decisions can be made taking into account economic, market, supply, and system uncertainties. The research is based on a real business case in the Oriented Strand Board (OSB) industry. The computational results show that the proposed approach provides realistic and robust solutions. For the case considered, the planning method elaborated yields significant performance improvements over the solutions obtained from the mixed integer programming model previously suggested for S&OP.

We study the supply chain tactical planning problem of an integrated furniture company located in the Province of Québec, Canada. The paper presents a mathematical model for tactical planning of a subset of the supply chain. The decisions concern procurement, inventory, outsourcing and demand allocation policies. The goal is to define manufacturing and logistics policies that will allow the furniture company to have a competitive level of service at minimum cost. We consider planning horizon of 1 year and the time periods are based on weeks. We assume that customer's demand is known and dynamic over the planning horizon. Supply chain planning is formulated as a large mixed integer programming model. We developed a heuristic using a time decomposition approach in order to obtain good solutions within reasonable time limit for large size problems. Computational results of the heuristic are reported. We also present the quantitative and qualitative results of the application of the mathematical model to a real industrial case.

In theory, linkages between hierarchical forest management planning levels ensure coherent disaggregation of long-term wood supply allocation as input for short-term demand-driven harvest planning. In practice, these linkages may be ineffective, and solutions produced may be incoherent in terms of volume and value-creation potential of harvested timber. Systematic incoherence between planned and implemented forest management activities may induce drift of forest system state (i.e., divergence of planned and actual system state trajectories), thus compromising credibility and performance of the forest management planning process. We describe hierarchical forest management from a game-theoretic perspective and present an iterative two-phase model simulating interaction between long- and short-term planning processes. Using an illustrative case study, we confirm the existence of a systematic drift effect, which we attribute to ineffective linkages between long- and short-term planning. In several simulated scenarios, the planning process fails to ensure long-term wood supply sustainability, fails to reliably meet industrial fiber demand over time, and exacerbates incoherence between wood supply and fiber demand over several planning iterations. We show that manipulating linkages between long- and short-term planning processes can reduce incoherence and describe future work on game-theoretic planning process model formulations that may improve hierarchical planning process performance., En théorie, les systèmes de planification hiérarchiques intègrent des mécanismes de liaison efficaces, assurant ainsi une désaggrégation cohérente de l'attribution de volumes aux usines lors de la planification détaillée des opérations de récolte. En pratique, les mécanismes de liaison entre la planification à long- et à court-terme peuvent être inefficaces, menant donc à des plans incohérents en termes du volume récolté, de la représentation des essences, et du potentiel de création de valeur des billes livrées aux usines. Cette incohérence entre la planification et l'exécution de la récolte peut induire une dérive systématique de l'état du système forestier (c.-à-d. divergence entre les trajectoires projetées et réalisées), compromettant donc la crédibilité et la performance du processus de planification de l'aménagement forestier. Nous décrivons le processus de planification forestière en termes de la théorie du jeu, et nous simulons l'interaction entre la planification de l'approvisionnement et la planification de la récolte à l'aide d'un modèle itératif à deux phases. Nous présentons une étude de cas, et nous montrons l'existence d'un effet de dérive systématique, que nous attribuons à l'innefficacité des mécanismes reliant la planification long- et court-terme. Nous montrons qu'il est possible d'améliorer la cohérence des plans en manipulant les mécanismes de liaison, et proposons des avenues de recherche futures pouvant potentiellement améliorer la performance du processus de planification hiérarchique à l'aide de nouvelles formulations de modèles basés sur la théorie du jeu.

Current industrial trends favor distributed manufacturing with extensive use of subcontracting. In this context we present a two—level decision support system for operations scheduling where a set of firms (subcontractors) is competing for the realization of the manufacturing operations pertaining to a product. We consider the case where operation precedences are given in form of an assembly tree. Each firm bidding for an operation specifies a start time, a processing time, a production cost together with a storage cost for storing the work-in-process resulting from that operation beyond its completion time. At the first level, IBIS, an information support system is used for bid preparation based on resource usage, production requirements and production operations costs. At the second level, given the bids we present a procedure for finding the assignment of operations to firms that minimizes production and storage costs., La tendance actuelle favorise la fabrication répartie et la sous-contractance. Dans ce contexte, nous présentons un système à deux niveaux pour l'ordonnancement des tâches dans lequel un ensemble d'entreprises (les sous-contractants) sont en concurrence pour la réalisation des tâches menant aux produits. Nous considérons le cas où les contraintes de précé- dences sont données sous forme d'arbres d'assemblage. Chaque firme candidate pour une tâche donne le temps de début, le temps de fabrication, les coûts de production et de stockage des en—cours résultant de ces opérations. Au premier niveau, IBIS, un système d'information est utilisé pour la préparation des propositions de travail, il prend en compte l'utilisation des ressources, les besoins de production et les coûts de fabrication. Au deuxième niveau, étant donné les propositions, nous proposons une procédure pour trouver les affectations des tâches aux entreprises qui minimisent les coûts de production et de stockage.

This article investigates the robustness of different tactical planning and control policies for a softwood supply chain using an agent-based environment that simulates a distributed advanced planning and scheduling system and its corresponding supply chain operations. Simulations were modelled using a novel agent-based methodology combined with a robust experimental design approach and an industrial data set obtained from two companies in Eastern Canada. Experimental results provide insights about the dynamic relations among factors related to control levels, planning methods and planning horizon lengths. Results indicate that supply chain control levels play a relevant role in defining robust service levels, while the planning horizon and the planning method have lower impact in this context. In addition, from the supply chain inventory level point of view, we verified that the three investigated tactical rules have to be configured together if one desires to maximise their contribution for a robust supply chain system capable of coping with uncertainties from the business environment. When these rules are evaluated individually, it is not possible to make the most of their potential due to interactions between them. The article concludes by proposing an optimum robust configuration of the tactical rules to minimise the impact of supply chain uncertainties

In today's industrial context, competitiveness is closely associated to supply chain performance. Coordination between business units is essential to increase this performance, in order to produce and deliver products on time to customers, at a competitive price. While planning systems usually follow a single straightforward production planning process, this paper proposes that partners adapt together their local planning process (i.e. planning behaviours) to the different situations met in the supply chain environment. Because each partner can choose different behaviour and all behaviours will have an impact on the overall performance, it is difficult to know which is preferable for each partner to increase their performance. Using agent-based technology, simulation experiments have been undertaken to verify if multi-behaviour planning agents who can change planning behaviours to adapt to their environment can increase supply chain performance. These agents have been implemented in an agent-based planning platform, using a case study illustrating a lumber supply chain. The performance analysis shows that advanced planning systems can take advantage of using multiple planning processes, because of the dynamic context of supply chains.

Fine paper mills produce a variety of paper grades to satisfy demand for a large number of sheeted products. Huge reels of different paper grades are produced on a cyclical basis on paper machines. These reels are then cut into rolls of smaller size which are then either sold as such, or sheeted into finished products in converting plants. A huge number of roll sizes would be required to cut all finished products without trim loss and they cannot all be inventoried. An assortment of rolls is inventoried with the implication that the sheeting operations may yield trim loss. The selection of the assortment of roll sizes to stock and the assignment of these roll sizes to finished products have a significant impact on performances. This paper presents a model to decide the parent roll assortment and assignments to finished products based on these products demand processes, desired service levels, trim loss and inventory holding costs. Risk pooling economies made by assigning several finished products to a given roll size is a fundamental aspect of the problem. The overall model is a binary non-linear program. Two solution methods are developed: a branch and price algorithm based on column generation and a fast pricing heuristic, and a marginal cost heuristic. The two methods are tested on real data and also on randomly generated problem instances. The approach proposed was implemented by a large pulp and paper company.

A stochastic programming model for designing logistics networks integrating reverse logistics into current supply chains is proposed in this paper. It aims at evaluating impacts of randomness related to recovery, processing and demand volumes on the design decisions. These decisions deal with the location of service and processing centres and warehouses, regarding processed products with reuse potential, the definition of mission of sites and, consequently, the product accessibility. Flows of recovered products may be directed toward one or a number of processing alternatives, according to the different states of the recovered products as well as to the network conditions, which relate to recovery and demand volumes with respect to capacity constraints and operating costs. Notably, recovered products may be repaired, disassembled for part refurbishing or disposed. Such products are indicated here as valorized products and represent an economical supply alternative, which meets lower quality standards in comparison with new products. Portions of needs fulfilled by valorized products are defined according to the requirements of end-users, as well as management policies and strategies. The model aims at improving valorized product accessibility, while reducing the total operating costs of such a network. A heuristics based on the sample average approximation, involving the Monte Carlo sampling methods, is proposed to solve the problem.

Strategic forest management planning models designed to maintain existing carbon stocks and maximize capacity for future sequestration can help identify underused opportunities to increase carbon stocks without diminishing other forest products. This study proposed a carbon stock unit that allows summing up the stocks in the different forest pools even if the decomposition far exceeds the planning horizon. This unit is used to integrate the methods and algorithms from the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) model into a wood supply model. The resulting model could be used to predict changes in carbon stocks, transfers between carbon pools, and greenhouse gas emissions that would result from every forest management activity. We tailored this model to meet different strategies: maximizing carbon storage in the forest, maximizing high-sustained timber yield, and achieving the dual objectives of yield and carbon storage. A range of management scenarios were simulated using the data of a 485,000 hectares mixed-wood forest in Quebec, Canada. Our results demonstrate that, with the reduction in the harvest rates, the increase in the ecosystem carbon storage is insufficient to offset the carbon losses associated with the increase in the harvest rates. Study Implications: In this article, we adopt the perspective of forest managers who contend that removing lumber from the forest can be achieved in a responsible way or in a way that does not affect the carbon stocks in the forest in the long term. We propose a model that integrates methods and algorithms from the CBM-CFS3 model to simulate carbon dynamics of aboveground and belowground biomass and dead organic matter, including soils. The model can be used to predict carbon storage potential within a forest region assuming a given management strategy. We used data of a large forest area to develop a number of sophisticated scenarios of strategic forest planning. Our results are consistent with the for

The bullwhip effect is an amplification of the variability of the orders placed by companies in a supply chain. This variability reduces the efficiency of supply chains, since it incurs costs due to higher inventory levels and supply chain agility reduction. Eliminating the bullwhip effect is surely simple; every company just has to order following the market demand, i.e., each company should use a lot-for-lot type of ordering policy. However, many reasons, such as inventory management, lot-sizing, and market, supply, or operation uncertainties, motivate companies not to use this strategy. Therefore, the bullwhip effect cannot be totally eliminated. However, it can be reduced by information sharing, which is the form of collaboration considered in this paper. More precisely, we study how to separate demand into original demand and adjustments. We describe two principles explaining how to use the shared information to reduce the amplification of order variability induced by lead times, which we propose as a cause of the effect. Simulations confirm the value of these two principles with regard to costs and customer service levels.

This article provides a conceptual framework for the design and management of value loops. A value loop is a logistics network that integrates reverse logistics activities related to the recovery of unused products, their retransformation and the redistribution of the reusable materials. The conceptual framework is elaborated based on the business process re-engineering experience for the wheelchair allocation, maintenance, recovery, retransformation and redistribution context in the Province of Quebec, Canada, governed and managed by a government agency. This framework addresses all the significant generic decisional levels, from the identification of the customers’ expectations or needs, to the design and management of the logistics networks, processes and products from a life cycle perspective, to activity planning and scheduling. The decisional levels are mainly characterised according to the reverse logistics activities. Their implementation is illustrated within the wheelchair context in the Province of Quebec. A brief discussion on the roles of the involved network parties is made from this context.

This paper introduces a strategic framework for designing and operating agile manufacturing networks, enabling to collaboratively plan, control and manage day-to-day contingencies in a dynamic environment. It is based on a distributed collaborative vision of manufacturing systems. We first introduce a network-oriented organizational strategy according to which a manufacturing business dynamically organizes its operations through the configuration and activation of a distributed network of interdependent responsible manufacturing centers. Then, we present a collaborative relationships strategy as a contractual approach to implement operational networks. Finally, we introduce an operational strategy, showing how this networked collaborative approach can be used to manage day-to-day activities and contingencies in a close-to-reality manner. The concepts underlying the strategic framework are illustrated using a simplified case inspired by our manufacturing partner, a world-class motorcoach manufacturer.

Many research initiatives carried out in production management consider process planning and operations scheduling as two separate and sequential functions. However, in certain contexts, the two functions must be better integrated. This is the case in divergent production systems with co-production (i.e. production of different products at the same time from a single product input) when alternative production processes are available. This paper studies such a context and focuses on the case of drying and finishing operations in a softwood lumber facility. The situation is addressed using a single model that simultaneously performs process planning and scheduling. We evaluate two alternative formulations. The first one is based on mixed integer programming (MIP) and the second on constraint programming (CP). We also propose a search procedure to improve the performance of the CP approach. Both approaches are compared with respect to their capacity to generate good solutions in short computation time.

In this paper, we address the problem of defining the production campaigns on a paper machine. Each campaign is of a fixed duration (cycle time) and produces batches (lot sizes) of all or a set of the products. This paper presents a real case study discussing a specific lot sizing problem where a predetermined production sequence must be maintained. We propose a new approach where we compute first the cycle time by assuming constant demand, and then lot sizes are determined for each product within each cycle in order to satisfy demand. Finally, studying the context of a Canadian paper maker, we evaluate the impact of planning production under a cycling manner.

Profit-driven order promising mechanisms have been receiving increasing attention from academia and practitioners in recent years. In spite of the recent advances in the field, its application in practice still remains a challenge. One of the most interesting approaches currently discussed is called aATP (allocated available-to-promise). In this paper, we propose some advances for current state-of-the-art aATP constructions in make-to-stock environments, mainly adapting it to commodity products sold through spot markets. Practical situations are tested through simulations supported by real data obtained from a major softwood manufacturer in Canada. Examples show that the proposed approach can increase the profitability of the producer.

During recent years, horizontal collaboration in logistics has gained attention because of achieved potential benefits such as cost reduction, an increase in fulfillment rates, and a decrease in CO2 emissions owing to reductions in traveled distances. Successful real-world cases, however, are rare since horizontal cooperation in logistics is not usually sustainable. This paper pays attention to this paradox of the lack of cases and discusses 16 identified practical issues that could explain this phenomenon. We propose a taxonomy composed of four categories categorizing the practical issues according to a value chain approach: design, planning and operations, market/business, and behaviors. Furthermore, we propose and discuss some measures to mitigate these problems.

The traditional approach to plan the forest products value chain using a combination of sequential and hierarchical planning phases leads to suboptimal solutions. We present an integrated planning model to support forest planning on the long term with anticipation of the impacts on the economic and logistic activities in the forest value chain on a shorter term, and we propose a novel optimization approach that includes acceleration strategies to efficiently solve large-scale practical instances of this integrated planning problem. Our model extends and binds the models implemented in two solver engines that have developed in previous work. The first system, called Logilab, allows for defining and solving value chain optimization problems. The second system, called Silvilab, allows for generating and solving strategic problems. We revisit the tactical model in Logilab and we extend the strategic model in Silvilab so that the integrated planning problem can be solved using column generation decomposition with the subproblems formulated as hypergraphs and solved using a dynamic programing algorithm. Also, a new set of spatial sustainability constraints is considered in this model. Based on numerical experiments on large-scale industrial cases, the integrated approach resulted in up to 13% profit increase in comparison with the non-integrated approach. In addition, the proposed approach compares advantageously with a standard LP column generation approach to the integrated forest planning problem, both in CPU time (with an average 2.4 factor speed-up) and in memory requirement (with an average reduction by a factor of 20).

In order to beat the competition, access new markets, and respect operational, social, and environmental constraints, enterprises establish collaborations with many other business entities. Furthermore, with costs and information sharing, organizations have the opportunity to optimize their logistics activities. However, each enterprise has its own objectives and typically makes its own planning decisions to meet these objectives. Therefore, it becomes crucial to determine how business entities will work together as well as the value of the collaboration. Specifically, it is necessary to identify how logistics activities will be planned and executed, who will take the leadership of the collaboration, and how benefits will be shared. In this article, we explain how to efficiently build and manage inter-firm relationships. Moreover, we propose five coordination mechanisms that contribute to ensure information sharing, the coordination of logistics activities, and the sharing of benefits. Case studies are used to demonstrate the utility of the framework.