Title: Optimisation of multi-stage supply chain systems by integrated simulation-variable neighbourhood search algorithm

Authors: Ali Azadeh; Ali Zahedi Anaraki; Sara Motevali Haghighi; Zahra Jiryaei; Fatemeh Nadarlou

Addresses: School of Industrial Engineering and Center of Excellence for Intelligent Based Experimental Mechanics, College of Engineering, University of Tehran, Iran ' School of Industrial Engineering and Center of Excellence for Intelligent Based Experimental Mechanics, College of Engineering, University of Tehran, Iran ' Department of Engineering, Esfarayen University, North Khorasan, Iran ' Department of Industrial Engineering, College of Engineering, University of Yazd, Iran ' Department of Industrial Engineering, College of Engineering, University of Tafresh, Iran

Abstract: In this paper, multi-stage supply chain systems (SCSs) controlled by kanban system are appraised a new simulation metaheuristics approach. In the kanban system, decision making is based on determination of batch size for each kanban. This paper simulates supply chain system regarding the costs under just-in-time (JIT) production philosophy. Since the adopted model is of backward type, the desired output is given in order to find the parameters and/or the structure of the model producing the output. This backward problem is non-analytic and often seems to be even more complex than the forward one. This paper applies genetic algorithm (GA) and variable neighbourhood search (VNS) to optimise the simulation model. A simple real-coded GA and VNS is presented and used to change the simulation model parameters. With each new set of parameters, a simulation run is performed. From the statistics gathered by running the simulation, a goal function is constructed to measure the quality of these parameters. GA and VNS and GA-VNS successfully provide a parameter set to demonstrate its capability to solve such difficult backward problems even in the area of complex simulation model optimisation specially when there is no prior knowledge of simulation model behaviour.

Keywords: supply chain management; SCM; just-in-time; JIT; computer simulation; supply chain optimisation; genetic algorithms; GAs; variable neighbourhood search; VNS; multi-stage supply chains; kanban; batch sizes.

DOI: 10.1504/IJSOM.2015.068699

International Journal of Services and Operations Management, 2015 Vol.21 No.1, pp.1 - 26

Published online: 10 Apr 2015 *

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