Evaluation of heuristics for scheduling in a flowshop: a case study

The problem of finding the best permutation schedule for a flowshop has engaged the attention of researchers for almost four decades. In view of its NP-completeness, the problem is not amenable to the development of efficient optimizing algorithms. A number of heuristics have been proposed, most of which have been evaluated by using randomly generated problems for a single measure of performance. However, real-life problems often have more than one objective. This paper discusses a live flowshop problem that has the twin objectives of minimizing the production run-time as well as the total flowtime of jobs. Five heuristics are evaluated in this study and some interesting findings are reported.