روش الگوریتم ژنتیک برای تشکیل سلول های دستگاه با مسیرهای جایگزین

In cellular manufacturing systems, study and optimization of machine cell formation (CF) problems have long drawn attention of researchers. Optimum CF results in reduction of overall processing time, material handling cost, labor cost, in-process inventories and number of set-ups requirements. Also, it simplifies process plans and improves product quality. Since the modern manufacturing machines in a cell are generally multifunctional, the processing of parts are performed following alternative processing routes. The objective of study is to determine the optimal alternative processing route in order to minimize the total intercellular movements of parts in CF problems. Intercellular movements of parts depend on many factors such as parts volume including batch size and number of batches, sequence of processes and routes of production. In this paper, a genetic algorithm heuristic is presented for the CF problem with multiple process routes, sequence of processes and parts volume. Computational experimentation was performed with five benchmark problems. The results demonstrate that the performance of the proposed approach in terms of total intercellular movements of parts and best route selection are either better or competitive with the well-known existing methods.