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Production and distribution scheduling optimisation in a three-stage integrated supply chain using genetic algorithm

Production and distribution scheduling optimisation in a three-stage integrated supply chain... This paper addresses an integrated P-D scheduling model arising in a three-stage supply chain, which involves three stages: a single vehicle after processing by different suppliers, manufacturers, distributors and consumers located in separate geographic regions. The contribution of this paper is to provide an integrated P-D scheduling under fixed departure times in supply chain with consideration of transportation fleet, integration of supplier-manufacturer. The mathematical model was proposed as a mixed integer programming and solved by CPLEX software in small-scale problems to validate the model. Given the complexity of the solution and NP-hard structure of the proposed problem, genetic algorithm was used to find quality solutions by MATLAB software. Finally, the results of research show that managers of the case study can deliver orders to customer in minimum time and cost. According to the results, the proposed algorithm (GA) has a desired level of quality in solving the P-D real problems. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Business Performance and Supply Chain Modelling Inderscience Publishers

Production and distribution scheduling optimisation in a three-stage integrated supply chain using genetic algorithm

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1758-9401
eISSN
1758-941X
DOI
10.1504/IJBPSCM.2020.108889
Publisher site
See Article on Publisher Site

Abstract

This paper addresses an integrated P-D scheduling model arising in a three-stage supply chain, which involves three stages: a single vehicle after processing by different suppliers, manufacturers, distributors and consumers located in separate geographic regions. The contribution of this paper is to provide an integrated P-D scheduling under fixed departure times in supply chain with consideration of transportation fleet, integration of supplier-manufacturer. The mathematical model was proposed as a mixed integer programming and solved by CPLEX software in small-scale problems to validate the model. Given the complexity of the solution and NP-hard structure of the proposed problem, genetic algorithm was used to find quality solutions by MATLAB software. Finally, the results of research show that managers of the case study can deliver orders to customer in minimum time and cost. According to the results, the proposed algorithm (GA) has a desired level of quality in solving the P-D real problems.

Journal

International Journal of Business Performance and Supply Chain ModellingInderscience Publishers

Published: Jan 1, 2020

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