Heuristics and genetic algorithms for minimizing makespan of assembly jobs

Assembly jobs can be seen as a more generalized version of traditional jobs. A traditional job refers to one with only sequential operations while an assembly job refers to one with additional assembly operations and complex product structures. This research proposes and compares genetic algorithms and heuristics for scheduling assembly jobs. The objective is to minimize the makespan (maximum completion time) of a given set of assembly jobs. Experiments have been conducted to compare the performance of the proposed algorithms. Results show that the heuristics perform better for test problems of larger size and the genetic algorithms perform better for smaller size problems.