Tabu Search for Scheduling Grouped Jobs on Parallel Machines

A job scheduling model of identical machines on parallel was addressed. The model assumes that a setup time is incurred when a machine changes from processing one type of parts to a different type of parts, and the scheduling objective is to minimize the sum of total flow time. This kind of problem is NP hard. Two optimal algorithm methods were esablished. The solution was analyzed by computational study. The comparisons of the solutions show that the Tabu Search combined with heuristic algorithm is more reliable and has abilities to solve larger scale practical problems.