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

De-Yun Wang, Olivier Grunder and Ke-Jun Zhu

International Journal of Industrial and Systems Engineering, 2016, vol. 22, issue 1, 17-35

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. (search for similar items in EconPapers)
Date: 2016
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