Ant colony optimization for automated storage and retrieval system

Bo Xing, Wen Jing Gao, Fulufhelo V. Nelwamondo, Kimberly Battle, Tshilidzi Marwala

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

In this work, we first propose an NP-hard combinatorial problem, that is, the storage and retrieve (S/R) machine travel path optimization for batch order picking (BOP). Successful solving this problem is valuable to many application areas such inventory items in logistics and work-in-process storage in manufacturing systems. And then, we investigate the feasibility of using ant colony optimization (ACO) meta-heuristics to address the proposed problem. Simulation tests are executed separately based on two ACO algorithms. Finally, the S/R machine operating performance measure index such as total travel distance and total travel time are employed to evaluate the experimental results achieved by different ACO algorithms. Experimental case study demonstrates the effectiveness and applicability of the selected ACO approaches to our proposed BOP problem.

Original languageEnglish
Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
DOIs
Publication statusPublished - 2010
Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 - Barcelona, Spain
Duration: 18 Jul 201023 Jul 2010

Publication series

Name2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

Conference

Conference2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Country/TerritorySpain
CityBarcelona
Period18/07/1023/07/10

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Applied Mathematics

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