A list-based threshold accepting method for job shop scheduling problems

Process plants typically produce a family of related products that require similar processing techniques. The most important problem encountered in such manufacturing systems is scheduling of operations so that demand is fulfilled within a pre-described time horizon imposed by production planning. The typical scheduling operation that process plants involve can be formulated as a general job shop scheduling problem. The aim of this study is to describe a new metaheuristic method for solving the job shop scheduling problem of process plants, termed as list-based threshold accepting (LBTA) method. The main advantage of this method over the majority of other metaheuristics is that it produces quite satisfactory solutions in reasonable amount of time by tuning only one parameter of the method. This property makes the LBTA a reliable and a practical tool for every decision support system designed for solving real life scheduling problems. The LBTA is described in detail, tested over classical benchmark problems found in literature and a while characteristic job shop scheduling case study for dehydration plant operations is presented.