Comparative Evaluation of Genetic Algorithm with Conventional Heuristics for Minimizing Makespan in Flow Shop Scheduling

Today's production planning and control strategies have to deal with an increasingly dynamic environment, shorter production cycles, customized products, smaller batches and technological constraints are some of the factors that stretch the actual job scheduling strategies to the limit. Number of optimization techniques are available to solve these type problems. Combinatorial optimization problems are too difficult to be solved optimally, and hence heuristics are used to obtain "good" solutions in reasonable time. Many optimization problems from the industrial engineering world, in particular the manufacturing systems are very complex in nature and quite hard to solve by conventional optimization techniques. The specific goal of this paper is to do a comparative evaluation of Genetic Algorithm with conventional heuristic algorithms. The Genetic Algorithm (G.A.) is a potentially powerful tool for solving complex optimization problems. In this paper, the heuristic procedures considered are (1) Palmer's algorithm (2) Dannenbring's Rapid Access algorithm (3) C. D. S. (Campbell dudek and smith) algorithm. The results are compared and evaluated for the objective of minimizing the makespan.