Distance matrix based heuristics to minimize makespan of parallel batch processing machines with arbitrary job sizes and release times

Abstract

Batch scheduling is prevalent in many industries such as burn-in operations in semiconductor manufacturing and heat treatment operations in metalworking. In this paper, we consider the problem of minimizing makespan on parallel batch processing machines in the presence of non-identical job sizes and arbitrary release times. Since the problem under study is strongly NP-hard (non-deterministic polynomial-time hard), we develop a number of efficient heuristics. In the proposed heuristics, several distance matrix based approaches are first developed to form batches and a scheduling technique is devised to assign the batches to parallel machines. The performance of the proposed heuristics is evaluated by comparing their results to a set of existing heuristic and meta-heuristic algorithms in the literature. The computational experiments show that the proposed heuristics are competitive with respect to solution quality. Moreover, the computational costs of the proposed heuristics are very little.