Title: Ant colony optimisation for the bi-objective due-date-setting problem in the multi-class make-to-order firm
Authors: Mahboobeh Honarvar; S. Kamal Chaharsooghi; Mohammad Modarres
Department of Industrial Engineering, Yazd University, Yazd, Iran
Department of Industrial Engineering, Tarbiat Modares University, Tehran, Iran
Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran
Abstract: In this study, we develop a bi-objective programming approach for due-date setting in make-to-order manufacturing with different classes of customers. We formulate the problem of quoting due-dates under the assumption that demand is dependent on lead-time and price is determined by the length of the delivery time. In addition, other parameters such as production policy, inventory holding, delivery system and capacity utilisation should be considered in due-date decisions. To this purpose, we consider additional objective function in traditional due-date management problem. So, the proposed bi-objective model attempts to maximise total profit and minimise rates of changes in capacity utilisation simultaneously. To obtain a set of Pareto solutions efficiently, we propose an algorithm based on multi-objective ant colony optimisation. The proposed algorithm is compared with a noticeable multi-objective genetic algorithm, i.e. SPEA, based on some comparison metrics with random instances.
Keywords: due dates; price; production; capacity utilisation; multi-objective ACO; ant colony optimisation; make-to-order manufacturing.
Int. J. of Industrial and Systems Engineering, 2013 Vol.13, No.4, pp.496 - 520
Available online: 14 Mar 2013