Minimizing total flow time for the worker assignment scheduling problem in the identical parallel-machine models

The worker assignment scheduling problem consists of two basic questions of job scheduling and worker assignment. In this study, only the performance measure of total flow time is investigated in the model of identical parallel-machine with nonpreemptive jobs. Because the worker assignment scheduling problem in this specific model can be shown as NP-complete, heuristics have been developed for minimizing the total flow time. This selected worker assignment scheduling problem is solved in two stages of job scheduling and worker assignment. The shortest processing time for A(i) part (SPT-A) heuristic is used for the stage of job scheduling. For the stage of worker assignment, the largest marginal contribution (LMC) procedure is used to minimize the total flow time. Two 100 I/P/n/m/W problems were simulated; results obtained by the heuristics are either optimal or near optimal. In conclusion, the heuristics developed have shown very impressive results quite efficiently.