IJE TRANSACTIONS A: Basics Vol. 31, No. 10 (October 2018) 1723-1733   

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Y. Zare Mehrjerdi, M. Alipour and A. Mostafaeipour
( Received: November 21, 2017 – Accepted in Revised Form: August 17, 2018 )

Abstract    In this paper, a mixed-integer linear programming model is proposed to integrate batch picking and distribution scheduling problems in order to optimize them simultaneously in an order picking warehouse. A tow-phase heuristic algorithm is presented to solve it in reasonable time. The first phase uses a genetic algorithm to evaluate and select permutations of the given set of customers. The second phase uses the route first-cluster method to obtain an effective schedule for a given permutation of customers. Computational experiments represent that integrated approach can lead to significant reduction in the makespan. Moreover, Empirical observations on the performance of the heuristic algorithm are reported.


Keywords    Warehouse, Order Picking System, Order Batching, Picker-to-Part Systems, Distribution Scheduling



در این مقاله، یک مدل برنامه ریزی خطی صحیح-مختلط به منظور یکپارچه سازی و بهینه سازی همزمان مسائل برداشت دسته ای سفارشات و توزیع سفارشات در یک انبار برداشت ارائه شده است. یک الگوریتم دو مرحله ای به منظور حل مدل در زمان قابل قبول طراحی شده است. در مرحله ی اول از الگوریتم ارائه شده، از یک الگوریتم ژنتیک به منظور ایجاد و ارزیابی توالی هایی از مشتریان استفاده می شود. در مرحله‌ی دوم از الگوریتم، از رویکرد مسیریابی اولین خوشه به منظور به دست آوردن یک برنامه ی زمان بندی مؤثر استفاده می شود. نتایج عددی نشان می دهد که یکپارچه در نظر گرفتن این دو مسأله می تواند باعث کاهش چشم گیری در زمان کل پاسخگویی به سفارشات مشتریان شود. همچنین، مشاهداتی که بر روی عملکرد الگوریتم ابتکاری انجام شده است، گزارش شده است.


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