1,459
Views
39
CrossRef citations to date
0
Altmetric
Articles

A multi-objective optimisation study for the design of an AVS/RS warehouse

Pages 1107-1126 | Received 01 Apr 2019, Accepted 19 Jan 2020, Published online: 04 Feb 2020
 

Abstract

This paper deals with a hierarchical solution approach for multi-objective optimisation of an autonomous vehicle-based storage and retrieval system (AVS/RS) warehouse design. As a result of recent technological and Industry 4.0 developments, industries tend to automise their facilities using systems such as AVS/RS, an intra-logistics system, mostly utilised by large distribution centres. Compared to a traditional crane-based automated storage and retrieval system (AS/RS), these systems are more advantageous for having a flexible travel pattern of autonomous vehicles, enabling the designer vary the number of vehicles in the system based on the changed demand environment. Since it may affect the initial and operational costs as well as the system efficiency significantly, it is important to decide on the right warehouse design at first for these systems. In this paper, a multi-objective optimisation solution procedure under a hierarchical approach for the design of an AVS/RS, by considering minimisation of two conflicting performance measures – average cycle time and average energy consumption per transaction – is presented. By this work, it is also aimed to attract the attention of practitioners for the significance of multi-objective performance optimisation. For the multi-objective optimisation, Pareto-optimal solutions are presented.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Türkiye Bilimsel ve Teknolojik Araştirma Kurumu [grant number 214M613] and The Scientific and Technological Research Council of Turkey and Slovenian Research Agency: ARRS [grant number 214M613].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 973.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.