「脆弱性(Vulnerability)」とは何か

Facility location and supply chain management - A review

https://findresearcher.sdu.dk:8443/ws/files/116118561/reverse_logistics.pdf

Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future

Introduction to stochastic programming

Green supply chain management: A review and bibliometric analysis

Merging Resilience and Sustainability in Supply Chain Design

In order to achieve sustainability, the design and planning of a supply chain has to fulfil economic, social and environmental objectives. Traditionally the design of supply chains has been based on economic objectives. As societal environment concerns grow, environmental aspects are also emerging, not only at the industry level, but also within the context of supply chain management. The investment towards logistics structures that consider both economic and environmental performance is nowadays an important research topic. However, much is still to be done. This paper, addresses the retrofit of supply chain networks where planning aspects are also considered. The supply chain network design and planning is modeled through a Resource-Task-Network (RTN) methodology. A mixed integer linear programming (MILP) multi-objective approach is developed, which attempts to simultaneously maximize the annual profit of the supply chain, taking into account the network retrofit, while environmental impacts are minimized. The environmental impacts are accounted for through the Eco-indicator 99 methodology. Profit and environmental impacts are balanced through the use of goal programming. The model applicability is illustrated through the solution of an example.

A goal programming approach for the retrofit of supply chain networks

Design and Planning of Green Supply Chains with Risk Concerns

In this paper we propose a multi-objective decomposition algorithm for the design of multipurpose batch plants, which avoids the direct solution of the fully detailed MILP model. Most of such design problems involve the maximization of the total revenue, as well as the minimization of the total cost. The way to deal with these two terms simultaneously is either to combine them into a single criterion (e.g., profit), or to define the efficient frontier that offers the optimal solutions by multi-objective optimization. In this work the latter approach, while more elaborate, was adopted, since the exploration of this frontier enables the decision maker to evaluate different alternative solutions. A combination of the proposed decomposition algorithm and the s-constraint method is employed, which supports the application of this approach to perform economic assessments. The proposed algorithm allows the identification of the plant topologies, scheduling, equipment design and storage policies, subject to the plant's cost minimization and revenue maximization. A comparative analysis is presented between the detailed model proposed by Pinto et al. (2008b) and the proposed algorithm.

A Decomposition Based Algorithm for the Design of Multipurpose Batch Facilities Using Economic Assessments

The design and management of waste recovery networks involves the consideration of both economical and environmental issues, for which the authors developed a general network model that embeds the eco-indicator 99 methodology. Practical problems, which were tackled, involved the modeling of wide geographical networks and as a consequence, the superstructures of the resulting optimization models are highly dimensional, presenting in addition an inherent combinatorial nature. Hence, the resulting mathematical formulations, typically MILP problems, may undesirably take a few hours of CPU time to solve and yet only fall within a tolerance, albeit acceptable, of the best solution possible. These tend to be, however, hard cases corresponding to extreme operating conditions, such as imposing a discretionary green behavior while maximizing return, or conversely, imposing a high return while aiming for minimal environmental damages. This work explores alternative approaches to reduce CPU times by orders of magnitude and thus opening the way to handle effectively real-sized networks. These include a heuristic method that may be used to further simplify those approaches based on the I-constraint method. Details of the implementation are described and results compared to solutions located along the Pareto front, obtained with the latter.

Ana Paula Barbosa-Póvoa

Papers

Merging Resilience and Sustainability in Supply Chain Design

A goal programming approach for the retrofit of supply chain networks

Design and Planning of Green Supply Chains with Risk Concerns

A Decomposition Based Algorithm for the Design of Multipurpose Batch Facilities Using Economic Assessments

An Efficient and Fast General Optimization Model for a Sustainable Recovery Network of Industrial Polluted Wastes