Recent Approaches for Treating Job-Shop Scheduling Problems with Multiple Objective Optimization (MOJSSP's)

Abstract

The job-shop scheduling problem refers to most problems found in a typical factory environment where different operations must be completed to complete a job. A number of jobs are processing at any one time on a number of machines. A schedule must be derived which aims to complete all jobs as quickly as possible on the given production plant. In classical job-shop scheduling problem (JSSP), n jobs are processed to be completed on m unrelated machines. Each job requires processing on each machine exactly once. For each job, technology constraints specify a complete, distinct routing which is fixed and known in advance. The processing times are sequence-independent, fixed and known in advance. Each machine is continuously available from time zero, and the operations are processed with preemption. The objective is to minimize the maximum completion time (makespan). The job-shop scheduling problem is strongly NP-hard and the solution procedures are based either on enumeration or on heuristics. For this problem,. a theoretical results have begun for the two-machines case and in a special three-machines case by S.M. Johnson and R. Bellman in 1954. The analytical results, for example, simple criterion, can be obtained by using heuristic methods or dynamic programming type