Abstract
Recently, as the diversification of demand and the progress of production technology result in a wider variety of products, the necessity of scheduling and inventory control is increasing. This paper deals with methods of solution for a job-shop scheduling problem considering the capacities of in-process buffers. To this problem, the authors have proposed three kinds of ways of modeling the problem, i. e., a disjunctive graph (DGR) model, a timed Petri net (TPN) model and a Gantt chart (GTC) model. The present paper proposes several methods of solution based on these models. First, to the DGR model, a conventional algorithm, e. g., a branch-and-bound method, for the ordinary job-shop scheduling problem is applied. Second, to the TPN model, a simulation-based algorithm on TPN, i. e., an algorithm to obtain an optimal schedule among non-delayed schedules by using the branch-and-bound method is proposed. Further, the TPN model is extended to be fit for the problem in repetitive production processes. Third, to the GTC model, both an algorithm to obtain an optimal schedule by using the branch-and-bound method and an algorithm to obtain an approximately optimal schedule by using the list-scheduling method are proposed. Finally, results of several computational experiments are presented, in which the effects of buffers on schedule are investigated numerically.
