hadi mokhtari - Assistant Professor, Department of Industrial Engineering, Faculty of Engineering, University of Kashan, Kashan Iran
ashkan mozdgir - PhD Candidate, Faculty of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran.

In many practical systems, configuration of assembly lines is fixed and designing a new line may be incurred huge amount of costs, and thereby it is not desirable for practitioners. Hence, in this paper we suggest a re-balancing optimization model of an existing assembly line in which a new demand related cycle time (CT) is needed. The objective is to re-schedule the tasks in order to reduce the current CT to the new required one such that two objectives are optimized: (i) minimization of the incurred costs and (ii) minimization of nonsmoothing of reconfigured line. To solve the considered problem, a differential evolution algorithm (DEA), as an effective meta-heuristic, is adopted. The algorithm is easy to implement and requires a few control parameters. It generally shows reliable and accurate performance. However, the user is required to set the values of control parameters for each problem which is a time consuming procedure. To overcome this drawback and enhance the performance of DEA, its parameters are optimized by the use of Taguchi method which is an efficient statistical technique for parameter design. The obtained results from computational experiments on benchmark instances show the effectiveness of suggested algorithm against other methods..

Differential Evolution, Assembly Lines, Scheduling of Work Station, Taguchi Method