Title: An optimal model of dynamic lot-sizing with transportation decision and an improved ACO algorithm
Authors: Yingjun Li; Zhixiang Chen
Addresses: Department of Management Science, School of Business, Sun Yat-Sen University, No. 135, West Xingang Road, Guangzhou 510275, China ' Department of Management Science, School of Business, Sun Yat-Sen University, No. 135, West Xingang Road, Guangzhou 510275, China
Abstract: In this paper, an optimal model of multi-item single-level dynamic lot-sizing considering transportation decision in manufacturing system is studied. In the model, it is assumed that the freight cost is proportional to the number of containers, and the objective is to minimise total cost of the setup cost, holding cost and freight cost. Since the model is a mixed integer programming and it is a NP hard problem. An improved ant colony optimisation (ACO) algorithm is proposed. The algorithm is the trade-off between the solution quality and computational time. The computational result shows that the proposed algorithm is feasible and efficient based on solution quality and computation time compared with Lingo optimisation software. Computation examples show that the algorithm has advantage over software Lingo11.
Keywords: industrial engineering; ant colony optimisation; ACO; capacitated lot sizing; transport costs; optimal modelling; dynamic lot sizing; manufacturing industry; setup costs; holding costs; freight costs; mixed integer programming.
International Journal of Industrial and Systems Engineering, 2016 Vol.22 No.2, pp.121 - 144
Available online: 26 Dec 2015 *Full-text access for editors Access for subscribers Purchase this article Comment on this article