Evaluation of scheduling techniques for solving flowshop problems with no intermediate storage

The flowshop scheduling problem with no intermediate storage was studied in this research. This problem, a modification of the classical flowshop scheduling problem, arises when a set of jobs, once started, must be processed with no wait between consecutive machines. Six methods were compared in terms of the quality and efficiency of the scheduling solutions they produced. The six methods were: the Gupta algorithm, the Szwarc algorithm, an integer linear programming method, the Campbell et al. algorithm, the Dannenbring rapid access with extensive search algorithm, and a mixed integer linear programming procedure. It was concluded that the two mathematical programming methods produced the best performance in terms of makespan. These two methods, however, used a far greater amount of computational time than the other four solution techniques. Producing moderately good results as far as quality of performance, the Gupta and the Szwarc algorithms were comparable with the Campbell et al. and the Dannenbring algorithms in terms of computational efficiency, but these latter two algorithms produced the poorest performance with respect to the quality of solutions.