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Scheduling Post-Distribution Cross-Dock under Demand Uncertainty | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 5، دوره 10، Special Issue ( Nonlinear Analysis in Engineering and Sciences)، اسفند 2019، صفحه 53-65 اصل مقاله (1.32 M) | ||
| نوع مقاله: Special issue editorial | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2019.4396 | ||
| نویسندگان | ||
| M. M. Nasiri1؛ M. Aliakbarnia Omran* 2؛ F. Jolai1 | ||
| 1School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran | ||
| 2Department of Industrial Engineering, Kish International Camp, University of Tehran, Tehran, Iran | ||
| تاریخ دریافت: 19 مرداد 1398، تاریخ بازنگری: 23 مهر 1398، تاریخ پذیرش: 21 آبان 1398 | ||
| چکیده | ||
| The system of distribution of goods and services, along with other economic developments around the world, is rapidly evolving. In the world of distribution of goods, the main focus is on making distribution operations more effective. Due to the fact that the cross-dock has the advantage of removing intermediaries and reducing the space required for the warehouse, it is worth considering. Among the methods of cross-docking, the post-distribution method is important in terms of uncertainty. Due to the importance of the issue of the post-distribution method in cross-dock, this paper addresses the uncertainty of demand in cross-docking. For this purpose, a linear programming model has been developed for post-distribution cross-dock, and then solved an example by the use of the meta-heuristic whale algorithm. After that, uncertainty enters the model and the robust counterpart of the model present based on the robust optimization approach with using interval and polyhedral collective inductive uncertainty set. The results shows the model could control the demand uncertainty in distance zero until 20 percent and the model does not let the changing of demand efforts considerably on the scheduling of the cross-docking. | ||
| کلیدواژه‌ها | ||
| Scheduling؛ post-distribution cross-docking؛ demand uncertainty؛ robust optimization approach؛ collective inductive uncertainty set | ||
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آمار تعداد مشاهده مقاله: 41,843 تعداد دریافت فایل اصل مقاله: 537 |
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