Many real-world production systems produce large-sized commodities. Due to the size of the production unit, it is typical to see that more than one worker is working on the same work-piece. This type of assembly line in which multiple workers operate on the same work-piece simultaneously is called multi-manned assembly line (MAL). In the classical multi-manned assembly line balancing problem (MALBP) the objective is to minimize the manpower needed to manufacture one product unit. Apart from the manpower, other cost drivers like wage rates or machinery are neglected in this classical view of the problem.
However due to the high competition in the current production environment, reducing the production costs and increasing utilization of available resources are very important issues for manufacturing managers. In this paper a cost-oriented approach is used to model the MALBP with the aim of minimizing total cost per production unit. A mathematical model is developed to solve the problem. Since the proposed model is NP-hard, several heuristic algorithms and a genetic algorithm (GA) are presented to efficiently solve the problem.
Parameters and operators of the GA are selected using the design of experiments (DOE) method. Several examples are solved to illustrate the proposed model and the algorithms.