A Modified Artificial Bee Colony Algorithm for Scheduling Optimization of Multi-aisle AS/RS System

Xiaohui Yan, Felix T.S. Chan, Zhicong Zhang, Cixing Lv, Shuai Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


A modified artificial bee colony algorithm is proposed for solving the scheduling optimization problem of multi-aisle automatic storage/retrieval system. The optimization model of the problem is analyzed and founded, in which the sequence constraint of tasks and calculation of the number of aisles are more realistic. According to the features of the problem, the encoding and decoding strategies for solutions to MABC algorithm are redesigned. Probability selection-based updating method is also introduced to enhance the neighborhood search and preserve the good fragments. The experimental results show that MABC can obtain better results than PSO and GA algorithm, and is a competitive approach for AS/RS scheduling optimization.

Original languageEnglish
Title of host publicationAdvances in Swarm Intelligence - 11th International Conference, ICSI 2020, Proceedings
EditorsYing Tan, Yuhui Shi, Milan Tuba
Number of pages10
ISBN (Print)9783030539559
Publication statusPublished - 13 Jul 2020
Event11th International Conference on Swarm Intelligence, ICSI 2020 - Belgrade, Serbia
Duration: 14 Jul 202020 Jul 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12145 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on Swarm Intelligence, ICSI 2020


  • Automatic storage retrieval system
  • Modified artificial bee colony
  • Scheduling optimization

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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