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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2005.02.005 Byline: Marc Poulin (a), Benoit Montreuil (a)(b)(c), Alain Martel (a) Keywords: Mass customization; Personalization; Supply chain design; Golf club industry Abstract: Competitive, open and global markets render the consumer more demanding towards manufacturers' offers. In the past, firms could be competitive by providing value in quality, price and quick delivery. In the new economy, with the coming of e-business, the personalization of products becomes a key competitive factor. Manufacturers need to develop capabilities to fulfill these personalization needs while still respecting price, quality and service. This is an enormous challenge since there are many possible personalization offers that a firm could propose, up to the extreme of delivering a distinct product to each client. An initial step towards developing the appropriate personalization offers and capabilities is the identification of the potential personalization offers and how they affect the key processes within the demand and supply network. The paper presents a framework comprising of eight personalization options that can be combined to form a complete personalized offer. It then contrasts their impact on the demand and supply network. It exploits the industry of golf irons for illustration purposes. Author Affiliation: (a) CENTOR Network Organization Technology Research Center, Laval University, Quebec, Canada (b) Canada Research Chair in Enterprise Engineering, Canada (c) Cisco-Bell Research Chair in E-Business, Canada

A skin cream containing the antiviral drug penciclovir appears to be effective in treating cold sores in the mouth, according to a study of 4,573 people. Cold sores are caused by a virus called herpes simplex and the medical name for cold sores is herpes simplex labialis.

A model for solving the dynamic lot-sizing problem with price changes and inventory holding costs is developed with results showing intuitive actions resulting from the heuristic usually leading to almost optimal solutions. Intuitive actions include accumulating stock at lower price just prior to price increases and cutting short on orders due to an imminent price decrease and extensive testing proves the model effective.

The sequential decision problem known as constrained, multi-item, stochastic, nonstationary lot sizing problem is considered. Specifically, the stochastic programming concept of rolling planning horizons is employed to recast it as a multi-period static decision problem under risk. A branch and bound algorithm for solving a deterministic version of the stochastic program is also developed.

The problem of allocating specific resources for partially interchangeable activities is examined. It is assumed that demand for the activities is approximated by highly correlated continuous random variables, while allocation of the specific resource is aimed at minimizing projected shortage costs. It is shown that such problem can be viewed as a primary stochastic program which can be transformed into an equivalent deterministic program.

Graphical modeling formalisms are used for systems analysis and design in several knowledge fields. In the past the graphs associated with a given formalism were produced by hand with the help of templates. Today, however, several computer-aided system modeling tools are available on the market and, in order to be useful, they must be able to quickly display large graphs automatically. Unfortunately, the problem of drawing an arbitrary graph on the plane is NP-hard for most practical drawing criteria. The objective of this paper is to develop heuristic procedures to automatically and timely display arbitrary forests and undirected graphs in an interactive, mouse-driven graphic environment on a micro-computer. A fast geometric algorithm to display a tree with vertices of varying and non-negligible dimensions is presented and a general graph drawing heuristic is derived. The latter is based on the generation of a spanning tree with special properties which can be used to compute the rectangular coordinates of the graph vertices. We conclude with an example and with some comments on the performance of our algorithms.

This paper studies the strategic problem of designing emergency supply networks to support disaster relief over a planning horizon. The problem addresses decisions on the location and number of distribution centres needed, their capacity, and the quantity of each emergency item to keep in stock. It builds on a case study inspired by real-world data obtained from the North Carolina Emergency Management Division (NCEM) and the Federal Emergency Management Agency (FEMA). To tackle the problem, a scenario-based approach is proposed involving three phases: disaster scenario generation, design generation and design evaluation. Disasters are modelled as stochastic processes and a Monte Carlo procedure is derived to generate plausible catastrophic scenarios. Based on this detailed representation of disasters, a multi-phase modelling framework is proposed to design the emergency supply network. The two-stage stochastic programming model proposed is solved using a sample average approximation method. This scenario-based solution approach is applied to the case study to generate plausible scenarios, to produce alternative designs and to evaluate them on a set of performance measures in order to select the best design. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

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 day-to-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. [ABSTRACT FROM AUTHOR]

This paper presents a market-driven approach to design production-distribution networks for the lumber industry. The approach is developed to tackle a vast array of issues, from the adaptation of an enterprise supply chain to its evolving environment, such as changing forest policies, to enterprise rationalizations through mergers or acquisitions. The methodology takes into account the specificity of the industry divergent manufacturing processes as well as the lumber market segmentation into contracts, vendor managed inventory (VMI) agreements and spot markets. The approach is based on a comprehensive two-stage stochastic programming with recourse model. A sample average approximation (SAA) method based on Monte Carlo sampling techniques is proposed to solve this stochastic program, and it is shown that this approach outperforms the use of a comparable deterministic model based on averages. Finally, the decision support system developed to implement the approach is used to show how it can contribute to dealing with strategic issues in the Eastern-Canadian lumber industry. Forest policy as well as acquisition and rationalization issues are analyzed through applications of the methodology to a virtual but realistic case called Virtu@l-Lumber. [ABSTRACT FROM AUTHOR]

This paper presents an optimization methodology to design a network of manufacturing facilities producing several products, with non-trivial bills of material, under deterministic demands. The mathematical programming model developed finds the optimal structure of the manufacturing network, it defines the mission of the selected facilities and it determines the technology and the capacity of each facility. The approach takes economies of scale and scope into account. The model is formulated, a solution method based on Bender's decomposition is derived and computational results are presented. [ABSTRACT FROM AUTHOR]

A synthesis of novel 3′-deoxy analogs of the anti-HBV agent entecavir (BMS-200475) was devised using regioselective ring opening of suitable cyclopentene epoxides as the key step. This versatile approach afforded access to an enantiomeric pair of carbocyclic nucleosides from a single chiral intermediate. [Copyright &y& Elsevier]

This paper develops rolling planning horizon policies to manage material flows in multi-echelon supply — distribution networks with relatively general stochastic demand processes and procurement, transportation, inventory and shortage cost structures. Initially, the problem is formulated as a stochastic program with recourse, and its deterministic equivalent program is approximated by a multi-echelon lot-sizing model based on "risk inflated effective demands." A DRP — decomposition of this approximate model, which can be used with planning time fences or allocation algorithms, is then introduced. The use of expediting actions is also discussed. Finally, through a set of simulation experiments, the solutions obtained with our planning policies are compared with the solutions given by a classical DRP approach using safety stocks. The results show that the approach proposed leads to significant improvements. [ABSTRACT FROM AUTHOR]

The search for an appropriate balance between the supply and demand of health care services is at the centre of the nurse staffing problem in hospitals. A shortage of nursing staff results in poor service and it has a detrimental effect on the quality of care; a surplus generates unproductive costs. In this paper, a budgeting method based on a mathematical programming model is proposed to support the elaboration of a nursing budget and its allocation to hospital units. The approach takes health care system policies and labour agreements into account. The context is explained and, after discussing the existing literature and the assumptions made, a stochastic programming model of the situation is derived and an algorithm to solve it is proposed. The paper concludes by showing, with an example, how the approach can be used to arrive at well balanced budgets. [ABSTRACT FROM AUTHOR]

Copyright of INFOR is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of INFOR is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Treatment for recurrent genital herpes using edoxudine 3% cream for 5 days was evaluated in 200 patients in a randomized, multicenter, double-blind, placebo-controlled, clinic-initiated trial. Lesion tenderness was predictive of and more sensitive and longer-lasting than the symptom of pain, Among patients receiving placebo, times to crusting (P = .043), cessation of investigator- observed signs (P = .005), lesion-associated signs (P = .02), and groin signs (P = .05) were longer in women. Edoxudine reduced viral shedding in men (mean 2.7 vs. 3.4 days, P = .009) and women (2.0 days vs. 3.5 days, P = .0001). Loss of investigator-observed signs (4.4 vs. 6.2 days, P = .002), investigator-observed lesion tenderness (P = .01), lesion signs (P = .02), groin adenopa-thy (P = .01), and tenderness (P = .01) occurred earlier in women taking edoxudine. Edoxudine was well-tolerated and reduced several signs of herpes in women. Its clinical role in recurrent genital herpes remains to be fully determined. [ABSTRACT FROM PUBLISHER]