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The Physical Internet (PI) offers an innovative approach to logistics networks, focussing on operational, digital, and physical interconnectivity through encapsulation, interfaces, and protocols. However, PI network can be complex to manage due to its dynamic structure and the need for routing protocols that adapt to continually evolving circumstances. This paper proposes a dynamic and reactive routing protocol for a PI sub-network, leveraging well-known Internet techniques, namely 'Route Request' and 'Route Reply'. The objective is to enable dynamic, self-starting, multi-hop routing among nodes, ensuring continuous connectivity even amidst network disruptions. Moreover, the protocol incorporates reactive assignment algorithms to address disruptions, such as product shortages and resource unavailability. Additionally, the protocol is innovative in considering each container and resource's preferences and local knowledge of the system's known state. To include preferences in decision-making, we incorporate the Technique for Order Preference by Similarity to Ideal Solution and goal programming. Finally, we use multi-agent simulation and real order data from two major French retail chains to evaluate the protocol's performance. Results showed improved routing robustness and efficiency amidst disruptions compared to state-of-the-art methods. Various scenarios have been examined to yield promising insights for future research and practical applications in the realm of the PI. [ABSTRACT FROM AUTHOR]

The concept of the Physical Internet (PI) has been introduced as a vision for globally efficient and sustainable logistics. Examining the activities of the PI since its foundation, enormous efforts can be recognised in the political and business spheres. Furthermore, the topic has received considerable attention from logistics and supply chain management scientists. In this context, a wide variety of dimensions of the PI concept has been investigated. In contrast to some existing qualitative literature reviews, this study focuses on a quantitative review methodology to provide a holistic overview of the PI concept and its underlying dimensions and interrelations. Based on bibliometric performance analysis and science mapping, this research maps and connects the extant PI literature landscape. In doing so, the most important journals, researchers, and institutions in the PI field are identified. Furthermore, eight research topics are grouped thematically, including PI benefits and the challenge of its operationalisation, carriers and shippers in the PI network, PI foundations, smart product-service systems and services, hyperconnected city logistics, information and communication technology requirements, modular PI containers, and organisation and control of PI hubs. Based on the clustering of existing research, the study concludes by providing directions for future research. [ABSTRACT FROM AUTHOR]

Urban freight logistics is a complex interaction of stakeholders, technology, and infrastructure that shapes the dynamics of city logistics networks. The need for efficiency, flexibility, and sustainability in urban logistics is paramount due to the unpredictability of order patterns and the dispersed nature of delivery points. However, traditional approaches often result in isolated stakeholder operations and limited collaboration, leading to underutilized resources and duplicated efforts. This paper proposes a framework for the operation of the Physical Internet (PI) in logistics, which aims to break down silos and foster collaboration to minimize environmental impact in cities. The PI envisions standardized, interconnected logistics operations akin to digital packets moving through a network of hubs. Collaborative distribution networks in urban freight and the PI share the goal of transforming isolated operations into interconnected systems. The symbiotic relationship between these concepts offers a promising solution to achieve sustainable, efficient urban logistics systems. The integration of the Physical Internet Framework and the Sustainable Urban Logistics Plan holds the potential to usher in a transformative era of collaboration, efficiency, and environmental responsibility, paving the way for a more sustainable future. [ABSTRACT FROM AUTHOR]

This paper presents the Smart Logistics Node concept, which combines the physical infrastructure of logistics nodes with digital systems to enhance collaboration. The Smart Logistics Node benefits from data sharing, supporting infrastructure, and Connected and Automated Transport (CAT) technologies. Based on a literature review on logistics nodes and CAT, we propose a general classification of Smart Logistics Nodes distinguishing upon the node function, degree of organisational (de-)centralisation, digital integration, and infrastructure support for automated driving. Then, we classify sixteen logistics nodes and find that high digital integration is common while automation is lacking. Further automation entails mixed traffic on public roads and requires organisational changes that do not always align with current business models. Our work supports the adoption of emerging technology at logistics nodes and the comparability of business cases. Ultimately, node authorities can use our concept and classification to draw a roadmap to develop CAT capabilities. [ABSTRACT FROM AUTHOR]

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Urban freight logistics is a complex interaction of stakeholders, technology, and infrastructure that shapes the dynamics of city logistics networks. The need for efficiency, flexibility, and sustainability in urban logistics is paramount due to the unpredictability of order patterns and the dispersed nature of delivery points. However, traditional approaches often result in isolated stakeholder operations and limited collaboration, leading to underutilized resources and duplicated efforts. This paper proposes a framework for the operation of the Physical Internet (PI) in logistics, which aims to break down silos and foster collaboration to minimize environmental impact in cities. The PI envisions standardized, interconnected logistics operations akin to digital packets moving through a network of hubs. Collaborative distribution networks in urban freight and the PI share the goal of transforming isolated operations into interconnected systems. The symbiotic relationship between these concepts offers a promising solution to achieve sustainable, efficient urban logistics systems. The integration of the Physical Internet Framework and the Sustainable Urban Logistics Plan holds the potential to usher in a transformative era of collaboration, efficiency, and environmental responsibility, paving the way for a more sustainable future.

Current supply chain management (SCM) requires the control of physical and information flows in order to satisfy the customer, i.e. deliver the right product to the customer at the right place, at the right time, at the right price and at the lowest cost. SCM is inseparable from traceability which makes reliable the said flows, accelerates the transmission of information on these flows, allows to access a detailed knowledge of the movements, and makes the flows visible. In order to streamline and monitor, if possible, in real time and permanently these logistical processes, we propose the design and implementation of an Ontology-based traceability system based on an architectural model for the physical Internet using computing resources such as Cloud computing, Fog computing and Internet of Things (IoT) to achieve efficiency and sustainability goals. To evaluate our system, we were able to carry out all the queries that the user can express whether he is a customer, a supplier or a manager. [ABSTRACT FROM AUTHOR]

This study contributes to determining key attributes of the physical internet (PI) in circular economy (CE) as prior studies failed to explore the interrelationships among these attributes. The perspective of a CE is suitable to adopt the PI with an objective of obtaining global logistics networks formed on physical, digital and operational interconnectivity. This study attempts to propose a set of attributes in CE which is usually with qualitative analysis. The research results reveal multidisciplinary collaboration and technological advancement influence digital interoperability and physical infrastructure. Top criteria include Internet of Things, central orchestrator, alignment of resources, big data and blockchain. [ABSTRACT FROM AUTHOR]

The Physical Internet (PI) concept represents a paradigm shift in how logistics and supply chain management can be conceptualised and implemented. Through a meticulous literature review, this study maps the current state of PI research, spotlighting the necessity for a deeper dive into unexplored areas. The analysis reveals significant opportunities for enhancing logistic efficiency and sustainability, providing a foundation for future research and practical applications. This work invites scholars and industry practitioners to explore the transformative potential of PI. In the face of the dynamically evolving discussion on the Physical Internet, this article offers an in-depth analysis of the literature on this concept, shedding light on current research trends in this new face of logistics, challenges, and unexplored areas. The focus is on optimization models, collaboration, and system architecture, identifying knowledge gaps in areas of human impact on the management of the future logistics system and flows, legal aspects, financial management, economic feasibility, social and environmental effects, readiness for cooperation, security, and cultural differences. The literature review emphasizes the importance of PI for sustainable development and the goals of Industry 4.0, pointing to its potential role in transforming global logistic processes. By examining challenges, proposing solutions, and highlighting the potential of PI principles in improving logistic processes, this work constitutes a valuable resource for researchers, practitioners, and policymakers aiming to understand and implement the concept of the Physical Internet. [ABSTRACT FROM AUTHOR]

Background: The global logistics industry is facing looming challenges related to labor shortages and low-efficiency problems due to the lack of logistics facilities and resources, resulting in increased logistics delays. The Physical Internet is seen as a way to take logistics into the next generation of transformation. This research proposes a Physical Internet-enabled system that allows multiple companies to efficiently share warehouses and trucks to achieve operational efficiency and reduce CO2 emissions. Methods: We propose a novel demography-weighted combinatorial optimization model utilizing a genetic algorithm and the Lin–Kernighan heuristic. The model is tested with real data simulations to evaluate its performance. Results: The results show that compared to the existing model presented in a previous study, our proposed model improves location optimality and distributive routing efficiency and reduces CO2 emissions by 54%. Conclusions: By providing a well-founded novel model, this research makes an important contribution to the implementation of the Physical Internet by computing optimal logistics hubs and routes as well as providing a solution to cut CO2 emissions by half. [ABSTRACT FROM AUTHOR]

The delivery of goods (freight) accounts for the major cost and emissions in logistics systems worldwide. The effective management of the supply chain requires logistical efficiency and sustainability. Several logistics performance measurements such as distances driven and fuel efficiency are also indicators of sustainability. As an emerging paradigm, the Physical Internet (PI) addresses logistical, societal, and sustainability goals. However, the question remains whether some aspects of logistical efficiency in traditional logistics could be incorporated into the PI paradigm. To this effect, we examine how peddling, a consolidation strategy in traditional logistics, can enhance PI supply chain. Specifically, we formulate optimisation models and study the case of a Mexican automotive supply chain from both the PI and traditional logistics perspectives by comparing three different configurations; namely, Model P built on PI, Model S based on conventional standard peddling, and Model H, a hybrid. The hybrid Model H is optimised in a two-phase solution framework. We show via the case of a Mexican automotive supply chain that Model H outperforms others on average distance travelled and truck utilisation. Thereby, it is concluded that appropriate peddling and shipment consolidation policies may enhance PI supply chain logistics performance. [ABSTRACT FROM AUTHOR]

Like any other industry, transport faces major changes. This fact implies risks, but - at the same time – great opportunities for improvement and development. The triggers of change come from area of technology, customer’s fast changing requirements and new industry actors that disrupt traditional business models. This study is aimed to achieve two of these aspects: the requirements of retail customers (contractual conditions agreed with the suppliers of transport for distribution to the stores) and the impact of the new technologies. This article focus is on the main conditions that develops new skills and competencies for service companies and remodels the processes according to new technologies. The current analysis ‘scope is to highlight the future trends of the relations between the customer and the carriers and the additional competences they will have to acquire on the Romanian market. The used research method was contract analysis and interviews with participating companies.

Current supply chain management (SCM) requires the control of physical and information flows in order to satisfy the customer, i.e. deliver the right product to the customer at the right place, at the right time, at the right price and at the lowest cost. SCM is inseparable from traceability which makes reliable the said flows, accelerates the transmission of information on these flows, allows to access a detailed knowledge of the movements, and makes the flows visible. In order to streamline and monitor, if possible, in real time and permanently these logistical processes, we propose the design and implementation of an Ontology-based traceability system based on an architectural model for the physical Internet using computing resources such as Cloud computing, Fog computing and Internet of Things (IoT) to achieve efficiency and sustainability goals. To evaluate our system, we were able to carry out all the queries that the user can express whether he is a customer, a supplier or a manager.

Information integration and sharing in a standardized manner is crucial to enable visibility, coordination and synchronization of supply chain activities, i.e., traceability within and across several companies. Product traceability is an essential tool fully integrated in supply chain management which should not only allow identifying, tracing and tracking but also ensuring product safety and quality. It helps to utilize the resources optimally and makes reliable the information and physical flows, accelerates the transmission of information on these flows, allows accessing a detailed knowledge of the product movements, and leads to the more effective management of the supply chain. However, several difficulties hinder product traceability implementation and make it a challenging task, including diversity of stakeholders, semantic differences between the involved actors, and lack of a shared language leading to confusion and misunderstandings, which make information exchange difficult. Highly expressive systems and techniques are therefore required. The latter must be characterized by the ability to exchange relevant data between stakeholders in a timely, meaningful and coherent manner. In this paper, we propose the development of an Ontology-based traceability system. The ontology is based on an architectural model for the physical Internet using computing resources such as Cloud computing, Fog computing and Internet of Things (IoT). The proposed system provides a shared and common language which improves information exchanges among all stakeholders in supply chains. To evaluate its consistency and efficiency, we carry out several queries dealing with different scenarios of product traceability. The validation results indicate that the developed ontology has the expressivity needed to represent all the knowledge related to the product traceability domain, enabling interoperability among different actors. [ABSTRACT FROM AUTHOR]

Supply chains are complex, stochastic systems. Nowadays, logistics managers face two main problems: increasingly diverse and variable customer demand that is difficult to predict. Classical forecasting methods implemented in many business units have limitations with the fluctuating demand and the complexity of fully connected supply chains. Machine Learning methods have been proposed to improve prediction. In this paper, a Long Short-Term Memory (LSTM) is proposed for demand forecasting in a physical internet supply chain network. A hybrid genetic algorithm and scatter search are proposed to automate tuning of the LSTM hyperparameters. To assess the performance of the proposed method, a real-case study on agricultural products in a supply chain in Thailand was considered. Accuracy and coefficient of determination were the key performance indicators used to compare the performance of the proposed method with other supervised learnings: ARIMAX, Support Vector Regression, and Multiple Linear Regression. The results prove the better forecasting efficiency of the LSTM method with continuous fluctuating demand, whereas the others offer greater performance with less varied demand. The performance of hybrid metaheuristics is higher than with trial-and-error. Finally, the results of forecasting model are effective in transportation and holding costs in the distribution process of the Physical Internet. [ABSTRACT FROM AUTHOR]

The Physical Internet (PI) provides a solution for coping with the continuous rise in urban logistical demands by exploring same-level and cross-level paths. This research suggests a PI-based urban logistical distribution model based on PI distribution that minimizes transportation costs. It also intends to maintain the integrity of the logistical transportation process. This proposed model enhances the flexibility of goods operation and reduces the global cost of logistics' distribution using an interconnected and open PI logistics distribution mode. This model also explores the functional aspects of the operational problems of city logistical systems and relates to optimization problems. These functionalities are realized by the hierarchical functional structure and are characterized by different cost specifications. The proposed framework provides better integration and cooperation between city logistics warehouses and higher utilization level of logistical infrastructure. The experimental results show that the distribution cost of the PI logistics model is significantly better than that of a traditional logistics model. The elastic and cost advantages grow relatively as the infrastructure for distribution scales up and interruptions from emergencies occur. [ABSTRACT FROM AUTHOR]

This article proposes a Physical Internet-enabled customized furniture delivery system (PI-CFDS) with the following contributions. First, a set of PI-enabled smart logistics facilities was adopted to transform the conventional operations. A PI decision support platform was designed to deal with resource planning. Second, since the classical methods cannot be applied directly, we developed a new approach, including both mathematical modelling and algorithm design. The optimal planning decision maximizes the shipper's profits while providing a stable income for the carriers. Third, the proposed solution was verified via a real-life case study. The effects of geographical, cost, and demand parameters were also analyzed. Our results show that the PI-CFDS solution has advantageous over the traditional solution when considering the dispersed distribution of customer depots. We found that when the dispersion of customer locations increases, the fixed cost of vehicles increases, and the salary difference between drivers and movers increases; in this situation, the advantages of the PI-CFDS solution are more apparent. However, compared with the traditional solution, the PI-CFDS solution is more sensitive to the rise of fuel prices and the stability of demand. The results yield substantial insights and facilitate daily decision-making for managers. [ABSTRACT FROM AUTHOR]

The purpose of this study is to discover physical internet attributes for satisfying economic, social, and environmental benefits, and frame the hierarchical interrelationships of these attributes. The fuzzy Delphi method is used to define necessary criteria; fuzzy Decision-Making Trial and Evaluation Laboratory is adopted to identify the cause-and-effect relationships based on the experts’ viewpoints. Finding - The result also presents the most important criteria having causal effects on others including privacy preservation approaches, system of logistics network interconnectivity, distributed data storage, real-time locating system, and distributed multi-segment intermodal transport, from which recommend practical implications for the decision-making process. This study suggests both theoretical and managerial implications for improving the physical internet towards sustainable supply chain as physical internet has been perceived as a novel logistics model towards sustainability and a key solution for the current paradigms to overcome sustainable issues. This study contributes to the literature by pointing out the causal aspects for physical internet implementation, which are digital interoperability of supply chain, and shared warehouse and transportation networks.

Background: The global logistics industry is facing looming challenges related to labor shortages and low-efficiency problems due to the lack of logistics facilities and resources, resulting in increased logistics delays. The Physical Internet is seen as a way to take logistics into the next generation of transformation. This research proposes a Physical Internet-enabled system that allows multiple companies to efficiently share warehouses and trucks to achieve operational efficiency and reduce CO2 emissions. Methods: We propose a novel demography-weighted combinatorial optimization model utilizing a genetic algorithm and the Lin–Kernighan heuristic. The model is tested with real data simulations to evaluate its performance. Results: The results show that compared to the existing model presented in a previous study, our proposed model improves location optimality and distributive routing efficiency and reduces CO2 emissions by 54%. Conclusions: By providing a well-founded novel model, this research makes an important contribution to the implementation of the Physical Internet by computing optimal logistics hubs and routes as well as providing a solution to cut CO2 emissions by half.

This paper considers an incentive mechanism coupled with a set of collaborative rules in a decentralised collaborative transport network (CTN), taking the Physical Internet as an example. The goal of the proposed mechanism is to increase the efficiency, effectiveness, and sustainability of the network without decreasing the individual profit of the independent carriers. A multi-agent simulation model was developed to evaluate the performance of the proposed mechanism and rules and to analyse the impacts on the overall performance of the decentralised CTN. Moreover, two significant factors were identified and studied: network and market characteristics (e.g. demand to supply ratio), and competition between carriers. A baseline scenario with no collaboration was also simulated for comparison. The results indicate that collaborative rules are advantageous for all market types regardless of the competition in the network. This paper is among the first to investigate collaborative mechanisms and rules for decentralised CTN, especially with regard to sustainability issues. It also provides an effective methodology for designing mechanisms and rules in decentralised CTN, as well as for assessing performance. [ABSTRACT FROM AUTHOR]

Owing to its interconnections and open characteristics, Physical Internet (PI) has the potential to help companies meet the sustainability challenges. In this paper, to investigate the sustainability performance of the PI in an integrated production-inventory-distribution system, we propose a multi-objective mixed integer linear programming model (MOMILP) that encompasses all three dimensions of sustainability. The economic and environmental objectives are measured through the total cost and greenhouse gas (GHG) emissions, respectively. The social objective is captured by the impact of accident risk. Then, we solve the model by using the augmented ϵ-constraint method and compare the sustainability performance of the PI-enabled model with that of models enabled by the traditional (TR) and horizontal collaboration (HC) networks. The results show that the PI can not only improve the economic and environmental performance by increasing vehicle utilisation, but also alleviate the impacts of accident risks by avoiding risky routes. More interestingly, good compromise solutions featuring the PI can further improve the sustainability performance while guaranteeing the performance of the TR at the ideal point—something unachievable for the HC and TR. Moreover, sensitivity analyses demonstrate that the PI can still guarantee significant sustainability performance advantages under different common retailer quantities and network structures. [ABSTRACT FROM AUTHOR]

Scheduling can be defined as the allocation of available resources over time while optimising a set of criteria like early completion time of task, holding inventory, etc. The complexity of the scheduling problem, already known to be high, increases if dynamic events and disruptions are considered. In addition, in production and logistics, designers of scheduling systems must consider sustainability-related expectations. This paper presents an energy-efficient scheduling and rescheduling method (named Green Rescheduling Method, GRM). GRM aims at the solving of the dynamic scheduling problem under the condition of a certain level of routing flexibility enabling the reassignment of tasks to new resources. The key performance indicators integrated into the proposed GRM are effectiveness and efficiency-oriented. Applications concern the domains of production and logistics. In order to assess the proposed approach, experimentations have been made and results illustrate the applicability of GRM to build efficient and effective scheduling and rescheduling both for flexible manufacturing systems and inventory distribution systems in a physical internet network. A mathematical formulation for flexible job shop problem with energy consumption is also proposed using mixed Integer programming to evaluate the performance of the predictive part of GRM. [ABSTRACT FROM AUTHOR]

The Physical Internet (PI) envisions a global logistics system that integrates physical, digital and operational connections. This study aims to develop a hyperconnected logistic platform for heavy-duty machinery (HDM) in the composting industry by utilizing a systematic methodology. The proposed architecture consists of four layers: the Domain Model, the MBSE Model, the Information Sharing Model and the Agent-based Simulation Platform. The Domain Model analyzes the current situation and investigates stakeholder viewpoints, and the MBSE Model reduces complexity and describes mutual interactions between requirements and needs. The Information Sharing Model focuses on the information exchange among the main components, and the Agent-based Simulation Platform implements the proposed platform. The feasibility of the proposed architecture is demonstrated through a use case in Styria, Austria. Three simulation-based scenarios are analyzed, starting from the semi-hyperconnected approach up to the hyperconnected approach with PI vision integration. The results indicate that the hyperconnected platform is successful in serving all composting facilities, leveraging underutilized resources and promoting high-quality compost production. Thus, the platform provides support in a local, communal setting, resulting in enhancing the circular economy within the composting sector. Our efforts aim to contribute to the realization of the Physical Internet vision and promote composting to ultimately achieve a more sustainable future. [ABSTRACT FROM AUTHOR]

The Physical Internet (PI)-enabled hyperconnected order-to-delivery system (OTD) provides new solutions for sustainable supply chains from production perspectives. In this system, a PI-enabled hyperconnected manufacturing system is more closely tied with other functions through Internet-of-Things (IoT)-enabled machines for communication. In the OTD, the PI-enabled hyperconnected production–distribution system (PI-H) is modelled by multi-objective mixed-integer-nonlinear programming to evaluate sustainability. We develop an improved reference-point based non-dominated sorting genetic algorithm (I-NSGAIII) to solve practical-scale PI-enabled hyperconnected production-distribution scheduling problems, with the problem-specific solution expression and dynamic programming, subproblem-guided crossover and mutation strategies, and adaptive evolution mechanisms. I-NSGAIII’s performance advantages and PI-H’s sustainable advantages are validated through extensive experiments.

The resilience and sustainability of supply chains are facing new challenges due to the increasing complexity of supply chains. Compared to traditional supply chain networks, the Physical Internet (PI) has the potential to address sustainable development challenges and build resilient supply chain networks by providing interconnected and open logistics services. However, the interplay between resilience and sustainability has yet to be thoroughly explored in the PI-enabled supply chain literature. This paper aims to investigate the relationship between resilience and sustainability in PI-enabled supply chains. An innovative hybrid approach that combines the resilient-sustainable performance scoring method with mixed-possibilistic programming is proposed to trade-off and analyze the relationship between the two. Applying the concepts of resilience and sustainability to PI-enabled supply chains involves optimizing costs, sustainable performance, and resilience levels simultaneously. This enables coping with unforeseen disruptions from suppliers, plants, and PI hubs. The results of computational experiments have demonstrated that the PI-enabled supply chain exhibits stronger sustainable and resilience performance in dealing with random disruptions compared to traditional supply chains. The fruitful research yielded important management insights and practical implications, thereby contributing to the reinforcement of the literature on PI. [ABSTRACT FROM AUTHOR]

Hub-based relay networks for long haul trucking offer an opportunity to improve the work–life balance of drivers while simultaneously supporting faster delivery through near-continuous flow of containers from source to destination. In this paper, we develop a model for deciding hub location and sizing along with the routing of loads. Costs of hub construction and operation, transportation and penalties for multi-day driver trips are included. Both deterministic and two-stage stochastic programming models have been formulated in this paper. The goal is to determine the optimal hub and route decisions so that overall cost is minimised. A case study on the highway network for the Western United States demonstrates the computational tractability of the approach along with the importance of considering demand uncertainty. [ABSTRACT FROM AUTHOR]

To achieve socio-economic and environmental sustainability, utilization of existing capacities and assets has become a key challenge for the transportation sector. This challenge has been recognised by many scholars, policy makers and practitioners leading to a substantial body of new concepts and models. The rather parallel evolution of the Physical Internet (PI) and synchromodal transport presents an opportunity to improve the current unsustainable freight transportation, by inducing a positive modal shift from roads to rails and inland waterways, and improving service levels by better connecting production research with freight movement. This paper thus examines the synchromodal and PI state-of-the-art models together with their designs, methodologies and findings proposed in the scientific literature. The main objective is to assess and explore the correlations between these two concepts in order to understand how they can reinforce each other. Despite the integrated vision of the Alliance for Logistics Innovation through Collaboration in Europe, the findings of this paper yield no well-established interconnections in the scientific literature between PI and synchromodality as they both merely coexist in parallel and address different dimensions, scales and levels of abstraction. This paper thus identifies potential synergies, future research directions and critical questions to be considered by modellers, developers and policy makers. [ABSTRACT FROM AUTHOR]

In contrast to traditional supply chain networks, Physical Internet (PI) is an interconnected open global logistics network based on open PI hubs and standard PI-containers that has the potential to achieve ground-breaking improvements in integrated production-inventory-distribution management. In this paper, to quantify the advantages of PI from a cost performance perspective, we propose a mixed-integer linear programming (MILP) formulation for addressing the problem that combines an integrated production-inventory-distribution decision with PI, which has been addressed separately in the existing literature. The results of computational experiments show that while achieving a comparable or better service level, PI can achieve significant cost savings compared to a traditional supply chain network with a dynamic configuration and a hybrid configuration. Moreover, we investigate the impact of several problem parameter changes on the total costs under each network setting, and managerial insights are derived. [ABSTRACT FROM AUTHOR]

With the rising urbanization and booming e-commerce, traditional last-mile delivery systems fail to satisfy the need for faster, cheaper, and more environmentally friendly deliveries. Several new approaches are put forward as an alternative to classical delivery systems in this regard, yet none of them offers the same level of flexibility, capacity, reliability, and managerial control by itself. This paper proposes a new last-mile delivery model that combines several new approaches and technologies to address this issue. More precisely, we suggest using public transit as a backbone network completed by automated service points, crowd-shipping, and backup transfers with zero-emission vehicles to provide a low-cost and environmentally friendly express delivery service. The design problem for the envisioned system is formulated as a two-stage stochastic program, and a branch-and-price (BP) algorithm is devised to solve it. Taking advantage of the nearly decomposable structure that would emerge in possible real-world applications, our study presents the first example of using decomposition branching in a BP framework to enhance computational efficiency. Extensive computational studies and simulations with real-world data reveal valuable managerial insights for the proposed system and attest to the efficacy of the suggested methodology. Funding: This work was supported by Türkiye Bilimsel ve Teknolojik Araştirma Kurumu [Grant 218M605] and Bilim Akademisi. Supplemental Material: The online appendices are available at https://doi.org/10.1287/trsc.2022.1157. [ABSTRACT FROM AUTHOR]