cujse

Cankaya University Journal of Science and Engineering

2564-7954

Cankaya University

Engineering

Mühendislik

Using Segment-based Genetic Algorithm with Local Search to Find Approximate Solution for Multi-Stage Supply Chain Network Design Problem

Rafsanjani

Marjan Kuchaki

Eskandari

Sadegh

11 01 2013

10 2 04 15 2017

2009

Cankaya University Journal of Science and Engineering

Designing an optimal supply chain network (SCN) is an NP-hard and highly nonlinear problem; therefore, this problem may not be solved efficiently using conventional optimization methods. In this article, we propose a genetic algorithm (GA) approach with segment-based operators combined with a local search technique (SHGA) to solve the multistage-based SCN design problems. To evaluate the performance of the proposed algorithm, we applied SHGA and other competing algorithms to SCNs with different features and different parameters. The results obtained show that the proposed algorithm outperforms the other competing algorithms.

Designing an optimal supply chain network (SCN) is an NP-hard and highly nonlinear problem;therefore, this problem may not be solved efficiently using conventional optimization methods. In this article,we propose a genetic algorithm (GA) approach with segment-based operators combined with a local searchtechnique (SHGA) to solve the multistage-based SCN design problems. To evaluate the performance of theproposed algorithm, we applied SHGA and other competing algorithms to SCNs with different features anddifferent parameters. The results obtained show that the proposed algorithm outperforms the other competingalgorithms.

Supply Chain Network Genetic Algorithm Segment-based Operators Local Search

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