Selecting between Sequential Zoning and Simultaneous Zoning for Picker-to-parts Order Picking System Based on Order Cluster and Genetic Algorithm

被引:5
|
作者
Shen Changpeng [1 ]
Wu Yaohua [1 ]
Zhou Chen [2 ]
机构
[1] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Peoples R China
[2] Georgia Inst Technol, Sch Ind & Syst Engn, Atlanta, GA 30332 USA
基金
中国国家自然科学基金;
关键词
selecting; sequential zoning; simultaneous zoning; order cluster; genetic algorithm; picker-to-parts; ASSIGNMENT; STORAGE;
D O I
10.3901/CJME.2011.05.820
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The existing research of sequential zoning system and simultaneous zoning system mainly focuses on some optimization problems such as workload balance, product assignment and simulation for each system separately. But there is little research on comparative study between sequential zoning and simultaneous zoning. In order to help the designers to choose the suitable zoning policy for picker-to-parts system reasonably and quickly, a systemic selection method is presented. Essentially, both zoning and batching are order clustering, so the customer order sheet can be divided into many unit grids. After the time formulation in one-dimensional unit was defined, the time models for each zoning policy in two-dimensional space were established using filling curves and sequence models to link the one-dimensional unit grids. in consideration of "U" shaped dual tour into consideration, the subtraction value of order picking time between sequential zoning and simultaneous zoning was defined as the objective function to select the suitable zoning policy based on time models. As it is convergent enough, genetic algorithm is adopted to find the optimal value of order picking time. In the experimental study, 5 different kinds of order/stock keeping unit(SKU) matrices with different densities d and quantities q following uniform distribution were created in order to test the suitability of sequential zoning and simultaneous zoning to different kinds of orders. After parameters setting, experimental orders inputting and iterative computations, the optimal order picking time for each zoning policy was gotten. By observing whether the delta time between them is greater than 0 or not, the suitability of zoning policies for picker-to-parts system were obtained. The significant effect of batch size b, zone number z and density d on suitability was also found by experimental study. The proposed research provides a new method for selection between sequential zoning and simultaneous zoning for picker-to-parts system, and improves the rationality and efficiency of selection process in practical design.
引用
收藏
页码:820 / 828
页数:9
相关论文
共 37 条
  • [2] A literature review on the level of automation in picker-to-parts order picking system: research opportunities
    Vijayakumar, Vivek
    Sgarbossa, Fabio
    [J]. IFAC PAPERSONLINE, 2021, 54 (01): : 438 - 443
  • [3] The impact of order batching and picking area zoning on order picking system performance
    Yu, Mengfei
    de Koster, Rene B. M.
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2009, 198 (02) : 480 - 490
  • [4] Robot picker solution in order picking systems: an ergo-zoning approach
    Sgarbossa, Fabio
    Romsdal, Anita
    Johannson, Finn H.
    Krogen, Torbjorn
    [J]. IFAC PAPERSONLINE, 2020, 53 (02): : 10597 - 10602
  • [5] THE IMPACT OF ITEM WEIGHT ON TRAVEL TIMES IN PICKER-TO-PARTS ORDER PICKING: AN AGENT-BASED SIMULATION APPROACH
    Elbert, Ralf
    Mueller, Jan Philipp
    [J]. 2017 WINTER SIMULATION CONFERENCE (WSC), 2017, : 3162 - 3173
  • [6] Order batching and batch sequencing in an AMR-assisted picker-to-parts system
    Zulj, Ivan
    Salewski, Hagen
    Goeke, Dominik
    Schneider, Michael
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2022, 298 (01) : 182 - 201
  • [7] AMR-Assisted Order Picking: Models for Picker-to-Parts Systems in a Two-Blocks Warehouse
    Pugliese, Giulia
    Chou, Xiaochen
    Loske, Dominic
    Klumpp, Matthias
    Montemanni, Roberto
    [J]. ALGORITHMS, 2022, 15 (11)
  • [8] Improved Adaptive Genetic Algorithm for Order Batching of “Part-to-picker” Picking System
    Li K.
    Liu T.
    Li W.
    [J]. Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2023, 59 (04): : 308 - 317
  • [9] Human–robot vs. human–manual teams: Understanding the dynamics of experience and performance variability in picker-to-parts order picking
    Koreis, Jonas
    [J]. Computers and Industrial Engineering, 2025, 200
  • [10] Planning a parts-to-picker order picking system with consideration of the impact of perceived workload
    Kumar, Suryakant
    Sheu, Jiuh-Biing
    Kundu, Tanmoy
    [J]. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2023, 173