رویکرد برنامه ریزی تولید چندمعیاره برای ماشین آلات برای مقاصد خاص
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|43662||2014||13 صفحه PDF||سفارش دهید||11404 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Production Economics, Volume 149, March 2014, Pages 89–101
This paper presents a multi-criteria master production scheduling approach as the final assembly of special purpose machines is known to be very cost intensive. These costs are mainly influenced by the master production schedule (MPS). Two major cost drivers arise. First, long assembly lead-times (up to several months) combined with high product values result in high capital commitments; thus, lead-times need to be minimized. Moreover, the factory calendar must be considered while calculating the MPS because the factory calendar can significantly influence the resulting lead-times. Second, contractual penalties and compensation costs arise if confirmed delivery dates cannot be kept. Therefore, resource requirements must be accounted for, and an MPS that is executable on the assembly shop floor must be calculated. To increase planning flexibility, we do not restrict the resource utilization with a formal constraint; instead, we introduce the additional objective of resource leveling. Consequently, the conflicting objectives lead-time minimization and resource leveling are integrated into a single objective function, in which the decision maker's preferences are represented by a weighting factor. To calculate such an MPS, we develop a tailor-made construction heuristic combined with a randomized variable neighborhood descent procedure. We evaluate our solution method by solving small instances with a commercial solver and large-scale instances from an application case of an aerospace company. Our results reveal that the decision maker's preferences are adequately reflected by the weighting factor. Moreover, we can provide a rule of thumb for selecting an appropriate initial weighting factor.