Mehdi Seifbarghy; Shima Zangeneh
Abstract
In the classic models of facility location, it is assumed that the selected facilities always work based on the schedule while, in the real world, facilities are always exposed to disruption risk and sometimes these disruptions have long-term effects on the supply chain network and cause a lot of problems. ...
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In the classic models of facility location, it is assumed that the selected facilities always work based on the schedule while, in the real world, facilities are always exposed to disruption risk and sometimes these disruptions have long-term effects on the supply chain network and cause a lot of problems. In this paper, a mixed integer programing (MIP) model presented in order to determine how to serve the customers at the time of disruption in distribution centers in a two-echelon supply chain, including distribution centers and customers. This model selects potential places that minimize traditionally supply chain costs and also the transportation cost after distribution centers disruptions. In fact, the model tries to choose the distribution centers facilities with lowest cost and highest reliability and also allocate them to customers. The problem divided into two sub-problems using Lagrangian relaxation approach. By examining sub-problems optimal conditions, a heuristic solution is used for the first sub-problem and a genetic algorithm is used for the second sub-problem to solve large-scale problems. Finally, numerical examples are presented to examine the performance and efficiency of the proposed model and approach
Milad Yari; Mir Saman Pishvaee; Armin Jabbarzadeh
Abstract
The main aim of this paper is to provide a model for supply chain design of decorative stones in competitive conditions by taking into account the risk of the disruption. The main tools used in this study are mathematical programming and game theory which Stackelberg game is often used for competitive ...
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The main aim of this paper is to provide a model for supply chain design of decorative stones in competitive conditions by taking into account the risk of the disruption. The main tools used in this study are mathematical programming and game theory which Stackelberg game is often used for competitive modeling. The aim of the proposed model is to consider potential risks of disruption and competitive situation in the market. Also, due to the problem situation, we use meta-heuristic methods like particle swarm optimization and biogeography based optimization for solving and verification of the model. The results show that the occurrence of disruption affects in location decisions of production and distribution centers, price of products and profit of chain components
