a cost-oriented model for multi-manned assembly line balancing problem

in many real world assembly line systems which the work-piece is of large size more than one worker work on the same work-piece in each station. this type of assembly line 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.