Title: A hybrid coding SA method for multi-item capacity-constrained production and delivery scheduling problem with arbitrary job volumes and customer inventory considerations

Authors: De-Yun Wang; Olivier Grunder; Ke-Jun Zhu

Addresses: Centre for Digital Business and Intelligent Management, School of Economics and Management, China University of Geosciences, Lumo Rd., Wuhan (430074), China ' IRTES – SET, UTBM, 90010 Belfort Cedex, France ' School of Economics and Management, China University of Geosciences, Lumo Rd., Wuhan (430074), China

Abstract: This article deals with an integrated scheduling problem for a multi-item capacity-constrained production and delivery system. The compatible jobs are firstly processed on a batching machine, and then delivered to a customer by one capacitated transporter. Each job has to be delivered to the customer before its due date. It is assumed that the job which arrives to the customer before its due date will occur an earliness penalty. The problem is to find an integrated schedule such that the total logistics cost is minimised while guaranteeing a certain customer service level. We formulate the problem as a nonlinear model, and show that this problem is intractable. Then we develop a hybrid-coding simulated annealing algorithm for solving the problem. At last, we derive a lower bound to verify performance of this proposed algorithm. Experiments show the efficiency in terms of both solution quality and running time of the proposed algorithm.

Keywords: simulated annealing; hybrid coding; production scheduling; delivery scheduling; systems engineering; arbitrary job volumes; customer inventory; capacity constraints; logistics costs; customer service levels; nonlinear modelling.

DOI: 10.1504/IJISE.2016.073258

International Journal of Industrial and Systems Engineering, 2016 Vol.22 No.1, pp.17 - 35

Available online: 30 Nov 2015 *

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