This study considers a parallel batch processing problem to minimize the makespan under constraints of arbitrary lot sizes, start time window and incompatible families. Wefirst formulate the problem witha mixed-integer programming model. Due to the NP-hardness of the problem, we develop a decomposition-based heuristic to obtain a near-optimal solution for large-scale problemswhen computational time is a concern.A two-dimensional saving function is introduced to quantify the value of time and capacity space wasted. Computational experiments show that the proposed heuristic performswell and can deal with large-scale problems efficiently within a reasonable computational time. For the small-size problems, the percentage of achieving optimal solutions by the DH is 94.17%,which indicates that the proposed heuristic is very good in solving small-size problems. For large-scale problems,our proposed heuristic outperformsan existing heuristic from the literaturein terms of solution quality
Relation:
International Journal of Industrial Engineering: Theory Applications and Practice 30(2), p.350-372
