فهرس المقالات Facility Location Problem

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  1 - Facility Location and Inventory Balancing in a Multi-period Multi-echelon Multi-objective Supply Chain: An MOEA Approach
  Seyed Habib A. Rahmati Abbas Ahmadi Behrooz Karimi
  A comprehensive and integrated study of any supply chain (SC) environment is a vital requirement that can create various advantages for the SC owners. This consideration causes productive managing of the SC through its whole wide components from upstream suppliers to do أکثر

  A comprehensive and integrated study of any supply chain (SC) environment is a vital requirement that can create various advantages for the SC owners. This consideration causes productive managing of the SC through its whole wide components from upstream suppliers to downstream retailers and customers. On this issue, despite many valuable studies reported in the current literature, considerable gaps still prevail. These gaps include integration and insertion of basic concepts, such as queuing theory, facility location, inventory management, or even fuzzy theory, as well as other new concepts such as strategic planning, data mining, business intelligence, and information technology. This study seeks to address some of these gaps. To do so, it proposes an integrated four-echelon multi-period multi-objective SC model. To make the model closer to the real world problems, it is also composed of inventory and facility location planning, simultaneously. The proposed model has a mixed integer linear programming (MILP) structure. The objectives of the model are reducing cost and minimizing the non-fill rate of customer zones demand. The cost reduction part includes cost values of raw material shipping from suppliers to plants, plant location, inventory holding costs in plants, distribution cost from plants to warehouses or distribution centers (DCs), and shipping costs from DCs to customer zones. Finally, since the literature of SC lacks efficient Pareto-based multi-objective evolutionary algorithms (MOEAs), a new multi-objective version of the biogeography-based optimization algorithm (MOBBO) is introduced to the literature of the SC. The efficiency of the algorithm is proved through its comparison with an existing algorithm called multi-objective harmony search (MOHS). تفاصيل المقالة
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  2 - A New Approach for Solving Fuzzy Single Facility Location Problem Under L1 Norm
  Nemat Allah Taghi-Nezhad Fatemeh Taleshian
  10.30495/fomj.2023.1989898.1100
  The location allocation problem is one of the most attractive optimization problems that is widely used in the real world. Therefore, any attempt to bring this problem closer to real-world conditions would be significant and useful. In this paper, we utilize fuzzy logic أکثر

  The location allocation problem is one of the most attractive optimization problems that is widely used in the real world. Therefore, any attempt to bring this problem closer to real-world conditions would be significant and useful. In this paper, we utilize fuzzy logic due to the uncertainty of parameters in the real world. That is the weights (the amounts of demands of customers) and variables (the coordinates of the optimal place) are both considered fuzzy numbers. If these variables are considered definitively, due to various conditions and reasons, it may not be possible to acquire land or build a facility center in it, so we also considered this variable in a fuzzy way and a facility center area was obtained, that certainly, the decision maker can find the right place more easily. To solve the fuzzy problem a new approach based on presenting the problem in the form of equivalent expressions is proposed. This equivalent problem is solved using fuzzy arithmetic. تفاصيل المقالة
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  3 - A hybrid DEA-based K-means and invasive weed optimization for facility location problem
  Farshad Faezy Razi
  In this paper, instead of the classical approach to the multi-criteria location selection problem, a new approach was presented based on selecting a portfolio of locations. First, the indices affecting the selection of maintenance stations were collected. TheK-means mod أکثر

  In this paper, instead of the classical approach to the multi-criteria location selection problem, a new approach was presented based on selecting a portfolio of locations. First, the indices affecting the selection of maintenance stations were collected. TheK-means model was used for clustering the maintenance stations. The optimal number of clusters was calculated through the Silhouette index. The efficiency of each cluster of stations was determined using the Charnes, Cooper and Rhodes input-oriented data envelopment analysis model. A bi-objective zero one programming model was used to select a Pareto optimal combination of rank and distance of stations. The Pareto solutions for the presented bi-objective model were determined using the invasive weed optimization method. Although the proposed methodology is meant for the selection of repair and maintenance stations in an oil refinery Company, it can be used in multi-criteria decision-making problems. تفاصيل المقالة