Hybrid Methods in Engineering

SOLVING FLEXIBLE FLOW SHOP PROBLEMS BY COMBINING LPT AND GUPTA SCHEDULING ALGORITHMS

ABSTRACT

Scheduling is an important process widely used in manufacturing, production, management, computer science, and so on. Appropriate scheduling not only reduces manufacturing costs but also reduces possibilities for violating due dates. Finding good schedules for given sets of jobs can thus help factory supervisors effectively control job flows and provide solutions for job sequencing. In simple flow shop problems, each machine operation center includes just one machine. If at least one machine center includes more than one machine, the scheduling problem becomes a flexible flow shop problem. Flexible flow shops can thus be thought of as generalizations of simple flow shops. In the past, Sriskandarajah and Sethi [6] proposed a heuristic algorithm for solving flexible flow shop problems for two machine centers. In this article, we extend their algorithm to solve flexible flow shop problems for more than two machine centers. The heuristic Gupta algorithm is adopted as the kernel for achieving this purpose. Because this problem is a nondeterministic-polynomial (NP)-complete problem, optimal solutions seem unnecessary, especially when the number of jobs is large.