Multi-objective optimisation model of shuttle-based storage and retrieval system

This paper presents a multi-objective optimisation solution procedure for the design of the Shuttle-Based Storage and Retrieval System (SBS/RS). An efficient SBS/RS design should take into account multi-objectives for optimization. In this study, the authors considered three objective functions in the design concept which are the minimization of average cycle time of transactions (average throughput time), amount of energy (electricity) consumption and total investment cost. By also considering the amount of energy consumption as an objective function for minimization, the authors aimed to contribute to an environmentally friendly design concept. During the optimization procedure, they considered seven design variables as number of aisles, number of tiers, number of columns, velocities of shuttle carriers, acceleration/deceleration of shuttle carriers, velocity of the elevators lifting tables and acceleration/deceleration of the elevators lifting tables. Due to the non-linear property of the objective function, the authors utilized the Non-Dominated Sorting Genetic Algorithm II (NSGA II) genetic algorithm for facilitating the solution. Lastly, they searched Pareto optimal solutions to find out the optimum results. They believe that this study provides a useful and a flexible tool for warehouse planners and designers, while choosing a particular type of SBS/RS at the early stage of the warehouse design.

  • Record URL:
  • Availability:
  • Supplemental Notes:
    • © 2016 Vilnius Gediminas Technical University (VGTU) Press 2016. Abstract reprinted with permission of Taylor & Francis.
  • Authors:
    • Borovinšek, Matej
    • Ekren, Banu Y
    • Burinskienė, Aurelija
    • Lerher, Tone
  • Publication Date: 2017-4

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 120-137
  • Serial:
  • Publication flags:

    Open Access (libre)

Subject/Index Terms

Filing Info

  • Accession Number: 01639373
  • Record Type: Publication
  • Files: TRIS
  • Created Date: May 31 2017 3:03PM