Multi-objective optimisation model of shuttle-based storage and retrieval system.
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| Titel: | Multi-objective optimisation model of shuttle-based storage and retrieval system. |
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| Autoren: | Borovinšek, Matej, Ekren, Banu Y., Burinskienė, Aurelija, Lerher, Tone |
| Quelle: | Transport (16484142); Jun2017, Vol. 32 Issue 2, p120-137, 18p |
| Schlagwörter: | MATHEMATICAL optimization, INFORMATION storage & retrieval systems standards, ELECTRICITY, ENERGY consumption, GENETIC algorithms |
| 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Transport (16484142) is the property of Vilnius Gediminas Technical University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Datenbank: | Complementary Index |
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