Optimization of a Multi-product Three-echelon Supply Chain مقالة

مؤلف: Najafi، M ؛ Ghodratnama، A ؛ Pasandideh، S.H.R ؛

Supply and Operations Management August 2017, Volume 4 - Number 3 (‎19 صفحة - من 229 إلی 247 )

الکلمات المفتاحية: Genetic Algorithm Three echelon supply chain Simulated annealing algorithm

خلاصة:

This paper aims at the single-objective optimization of multi-product for three-echelon supply chain architecture consisting of production plants, distribution centers (DCs), and customer zones (CZs). The key design decisions considered in the study include the quantity of products to be shipped from plants to DCs, from DCs to CZs , cycle length, and the production quantity so as to minimize the total cost .To optimize the objective, three-echelon network model is mathematically represented considering the associated constraints, production, capacity and shipment costs and solved using genetic algorithm (GA) and Simulated Annealing (SA).Some numerical illustrations are provided at the end to not only show the applicability of the proposed methodology, but also to select the best method using a t-test along with the simple additive weighting (SAW) method.

ملخص الجهاز:

Pasandideh a a Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran Abstract This paper aims at the single-objective optimization of multi-product for three-echelon supply chain architecture consisting of production plants, distribution centers (DCs), and customer zones (CZs). To optimize the objective, three-echelon network model is mathematically represented considering the associated constraints, production, capacity and shipment costs and solved using genetic algorithm (GA) and Simulated Annealing (SA). ‘Supply chain management is basically a set of approaches utilized to efficiently integrate suppliers, manufacturers, warehouses, and stores so that the merchandise is produced and distributed at the right quantities, to the right locations, and at the right time in order to minimize system-wide costs (or maximize profits) while satisfying service-level requirements’ (Simchi et al. Many of the problems that occur in supply chain optimization are combinatorial in nature and picking a set of optimal solutions in case of multi-objective formulations requires a algorithm that can efficiently search the entire objective space using small amounts of computation time. (2012) modeled a two-echelon single-product SC design problem as a bi-objective mixed-integer programming and studied the three variations of the classical ε-constraint methods to generate Pareto- optimal solutions. (2008) proposed a multi-objective stochastic programming approach for the supply chain network design problem in which demands, supplies, processing time, shortage, transportation, and capacity expansion costs were purposed uncertain. (2016) Bi-objective optimization of a three-echelon multi-server supply-chain problem in congested systems: Modeling and solution Computers & Industrial Engineering ,Vol. 99, pp.

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