Designing a Fuzzy Strategic Integrated Multiechelon Agile Supply Chain Network

Abstract

This paper integrates production, distribution and logistics activities at the strategic decision making level, where the objective is to design a multiechelon supply chain network considering agility as a key design criterion. A network with five echelons of supply chains including suppliers, plants, distribution centers, cross-docks, and customer zones is addressed in this paper. The problem has been mathematically formulated as a biobjective optimization model that aims to minimize the cost (fixed and variable) and maximize the plant flexibility and volume flexibility. A novel multiobjective parallel simulating annealing algorithm (MOPSA) is proposed to obtain the Pareto-optimal solutions of the problem. The performance of the proposed solution algorithm is compared with two well-known metaheuristics, namely, nondominated sorting genetic algorithm (NSGA-II) and Pareto archive evolution strategy (PAES). Computational results show that MOPSA outperforms the other metaheuristics.

On the Transformation Mechanism for Formulating a Multiproduct Two‐Layer Supply Chain Network Design Problem as a Network Flow Model

“…When the capacity of facilities is limited, the problem can be transformed into a facility location problem with certain capacity. The heuristic algorithm is mostly used to solve problems in multistage supply chain, especially when capacity constraints exist in all nodes, such as plants and DCs [14,15].…”