Assembly line balancing using genetic algorithms

Assembly Line Balancing (ALB) is one of the important problems of productio n/operations management area. As small improvements in the performance of t he system can lead to significant monetary consequences, it is of utmost im portance to develop practical solution procedures that yield high-quality d esign decisions with minimal computational requirements. Due to the NP-hard nature of the ALB problem, heuristics are generally used to solve real lif e problems. In this paper, we propose an efficient heuristic to solve the d eterministic and single-model ALB problem. The proposed heuristic is a Gene tic Algorithm (GA) with a special chromosome structure that is partitioned dynamically through the evolution process. Elitism is also implemented in t he model by using some concepts of Simulated Annealing (SA). In this contex t, the proposed approach can be viewed as a unified framework which combine s several new concepts of AI in the algorithmic design. Our computational e xperiments with the proposed algorithm indicate that it outperforms the exi sting heuristics on several test problems.