Title: Modelling for a joint production-distribution problem and its hybrid algorithm design

Authors: Jian Zhao; Hong Zhou; Chunhua Liang

Addresses: School of Economics and Management, Beihang University, Beijing, 100191, China; Software Technology College, Zhengzhou Institute of Aeronautical Industry Management, Zhengzhou, 450015, China ' School of Economics and Management, Beihang University, Beijing, 100191, China ' School of Economics and Management, Beihang University, Beijing, 100191, China

Abstract: With market globalisation, ignoring the dependencies of the functions of a supply chain can have costly consequences. As a result, companies are moving from decoupled decision making processes toward more collaborative design and control of all of their components. Constructing collaborative supply chain structures is crucial in gaining a sustainable competitive advantage. Therefore, in this paper, a three stages joint production-distribution problem in a supply chain consisting of a single manufacturer and multiple retailers is considered. The manufacturer produces multiple items on a single facility under a common horizon and delivers the finished products to its retailers. A single model is proposed to integrate production lot sizing, scheduling and finished goods distribution. The model is designed to find the production lot sizes, the delivery quantities and the production sequence of multiple items to minimise the sum of setup cost, holding cost, stock-out cost and distribution cost. A hybrid algorithm, integrating genetic algorithm, harmony search and tabu search, is designed to solve this problem. Based on two optimisation strategies, a numerical simulation experiment covering three different scaled problems is conducted to demonstrate the effectiveness of the proposed algorithm.

Keywords: production-distribution; integrated optimisation; genetic algorithms; harmony search; tabu search; modelling; hybrid algorithms; collaborative supply chains; supply chain management; SCM; lot sizing; scheduling; finished goods distribution; collaboration; integration; numerical simulation.

DOI: 10.1504/IJMIC.2013.051927

International Journal of Modelling, Identification and Control, 2013 Vol.18 No.1, pp.1 - 8

Available online: 05 Feb 2013 *

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