Simulation and optimization for batch order picking problem: the application of ant colony algorithm

  • Authors:

  • Bo Xing;Wen-Jing Gao;Kimberly Battle;Tshilidzi Marwala;Fulufhelo V. Nelwamondo

  • Affiliations:

  • University of Johannesburg, Johannesburg, South Africa;University of Johannesburg, Johannesburg, South Africa;University of Johannesburg, Johannesburg, South Africa;University of Johannesburg, Johannesburg, South Africa;Modeling and Digital Science Unit, Pretoria, South Africa

  • Venue:
  • Proceedings of the Winter Simulation Conference
  • Year:
  • 2010

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Abstract

This research deals with the batch order picking (BOP) problem in a man-on-board type of automated storage and retrieval system (AS/RS). When retrieval requests consist of multiple items and the items are kept in different locations, the storage/retrieval (S/R) machine must travel to various storage places to complete each batch of orders. In this article an ant colony optimization (ACO), in particular MAX-MIN ant system (MMAS) algorithm is employed for the resolution of BOP problems with multiple stock locations. Meanwhile a multi-agent simulation software called NetLogo is also used to demonstrate the importance of parameter selection in MMAS. The aim of this research is to minimize the total travel distance and travel time of S/R machine.