Cost-oriented parallel assembly line balancing problems: New models

In this thesis, the problem of balancing simultaneously parallel assembly lines with cost-oriented objective function is addressed. This problem is called cost-oriented parallel assembly line balancing problem. Several mixed integer programming models for cost-oriented parallel assembly line problems are proposed. Furthermore, a goal programming approach to balance parallel assembly lines with precise goals is proposed. Since the problem is well-known as NP-hard, a heuristic algorithm based on mathematical model and a hybrid parallel genetic algorithm are developed to solve the medium- and large-size scales problem. The proposed heuristic approaches are tested on the well-known benchmark problems in the literature, and performance of the approaches are compared with each other. The results of an experimental investigation show that the hybrid parallel genetic algorithm achieves significantly better solutions than other heuristic approach.