An effective heuristic for flow shop problems with total flow time as criterion

This research studies on application of genetic algorithms for flow shop problems with total flowtime as the criterion. There is still very little research focusing on total flow time for flow shop problems. We develop a genetic algorithm based heuristic for the problems, and use an integer programming model and an existing heuristic to evaluate the efficiency of the genetic algorithm based heuristic. We generate a set of problems with different numbers of machines, different numbers of jobs, and solve ten of each of the problems using the integer programming model, the existing heuristic, and the genetic algorithm based heuristic, respectively. The results are very encouraging and appear to indicate the genetic algorithms are efficient approaches for flow shop problems.