Share:


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

    Matej Borovinšek Affiliation
    ; Banu Y. Ekren Affiliation
    ; Aurelija Burinskienė Affiliation
    ; Tone Lerher Affiliation

Abstract

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, we 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, we aimed to contribute to an environmentally friendly design concept. During the optimization procedure, we 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, we utilized the Non-Dominated Sorting Genetic Algorithm II (NSGA II) genetic algorithm for facilitating the solution. Lastly, we searched Pareto optimal solutions to find out the optimum results. We 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.


First published online: 12 May 2016

Keyword : warehouses, shuttle-based storage and retrieval systems, multi-criteria optimization problem, performance analysis

How to Cite
Borovinšek, M., Ekren, B. Y., Burinskienė, A., & Lerher, T. (2017). Multi-objective optimisation model of shuttle-based storage and retrieval system. Transport, 32(2), 120–137. https://doi.org/10.3846/16484142.2016.1186732
Published in Issue
May 30, 2017
Abstract Views
1185
PDF Downloads
1062
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.