Order Batching Optimization for Warehouses with Cluster-Picking

被引：10

作者：

Aboelfotoh, Aaya ^{[1
]}

Singh, Manjeet ^{[2
]}

Suer, Gursel ^{[1
]}

机构：

[1] Ohio Univ, Dept Ind & Syst Engn, Athens, OH 45701 USA

[2] DHL Supply Chain, Solut Design, Westerville, OH 43082 USA

来源：

25TH INTERNATIONAL CONFERENCE ON PRODUCTION RESEARCH MANUFACTURING INNOVATION: CYBER PHYSICAL MANUFACTURING | 2019年 / 39卷

关键词：

order hatching; cluster picking; warehousing heuristics; pick efficiency; pick path; ANT COLONY OPTIMIZATION; TABU SEARCH; TRAVEL DISTANCE; WAVE PICKING; ALGORITHM; PICKERS; HYBRID;

D O I：

10.1016/j.promfg.2020.01.302

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper focuses on optimizing the static order batching problem (OBP) with multiple pickers. This problem involves optimal assignment of a set of customer orders to batches, given capacity constraints, in order to minimize the total distance travelled. The order picking strategy considered is cluster picking. We assume that each picker is assigned one batch and all pickers begin the pick tour simultaneously. The aim is to minimize the total distance travelled by all pickers, which is calculated based on the S-shape routing strategy. A mathematical model is developed to solve the OBP for small-scale instances. For larger instances, a simplified version of an order batching heuristic proposed by DHL Supply Chain is utilized and experimented with for different-sized problems. Both approaches are compared to the conventional first come first serve (FCFS) method of order batching. (C) 2019 The Authors. Published by Elsevier Ltd.

引用

页码：1464 / 1473

页数：10

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