Assembly lines are special flow-line production systems which are of great importance in industrial mass production. Since the flow time of a product in most industrial foundries dealing with heating products is important because of its cost, the present paper introduces the effect of task deterioration into the total flow time of a product in each production cycle of an assembly line. Task deterioration means that a task processed later consumes more time than the same task when it is processed earlier. This issue is considered in a simple assembly line balancing (SALB) problem, where the aim is to find an optimal schedule of tasks in the workstations so as to minimize total flow time of a product considering the desired cycle time. For this aim a mathematical model is proposed and, according to complexity of the considered problem, a heuristic algorithm is introduced to minimize the flow time objective function which is named as FTALB. Finally, several well-known examples are solved and comparisons are done with the popular genetic algorithm and tabu search meta-heuristics. The results show the effectiveness of the proposed FTALB heuristic algorithm in terms of both the quality of the solutions and the computational time, which is almost zero in all scales of instances.
This paper introduces the effect of task deterioration in simple assembly line balancing problem. In many realistic assembly lines, a deterioration task is considered when a task is started earlier than the assigned time since the station time is constant and the earliness of the task does not reduce the cycle time. This phenomenon is known as deteriorating tasks. Therefore, we seek an optimal assignment and schedule of tasks in workstations, in order to minimize the number of stations for a given cycle time, which is known as SALBP-1. For this purpose, a mathematical model is proposed. Since the pure SALBP-1 is proved to be NP-hard and considering task deterioration complicates problem further, we propose a genetic algorithm for solving such problem. Several well-known test problems are solved to study the performance of the proposed approach.
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