Zhang, H;
Guo, Z;
Zhang, W;
Cai, H;
Wang, C;
Yu, Y;
Li, W;
(2019)
Layout Design for Intelligent Warehouse by Evolution With Fitness Approximation.
IEEE Access
, 7
pp. 166310-166317.
10.1109/ACCESS.2019.2953486.
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Abstract
With the rapid growth of the express industry, intelligent warehouses that employ autonomous robots for carrying parcels have been widely used to handle the vast express volume. For such warehouses, the warehouse layout design plays a key role in improving transportation efficiency. However, this work is still done by human experts, which is expensive and leads to suboptimal results. In this paper, we aim to automate the warehouse layout designing process. We propose a two-layer evolutionary algorithm to efficiently explore the warehouse layout space, where an auxiliary objective fitness approximation model is introduced to predict the outcome of the designed warehouse layout and a two-layer population structure is proposed to incorporate the approximation model into the ordinary evolution framework. Empirical experiments show that our method can efficiently design effective warehouse layouts that outperform both heuristic-designed and vanilla evolution-designed warehouse layouts.
| Type: | Article |
|---|---|
| Title: | Layout Design for Intelligent Warehouse by Evolution With Fitness Approximation |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/ACCESS.2019.2953486 |
| Publisher version: | https://doi.org/10.1109/ACCESS.2019.2953486 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10091662 |
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