Establishing a Novel Algorithm for Highly Responsive Storage Space Allocation Based on NAR and Improved NSGA-III
Establishing a rapid-response mechanism to manage customer orders is very important in managing demand surges. In this study, combined with predicting order requests, we established a multiobjective optimization model to solve the warehouse space allocation problem. First, we developed a model based...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/4247290 |
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| _version_ | 1832549094496665600 |
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| author | Peijian Wu Yulu Chen |
| author_facet | Peijian Wu Yulu Chen |
| author_sort | Peijian Wu |
| collection | DOAJ |
| description | Establishing a rapid-response mechanism to manage customer orders is very important in managing demand surges. In this study, combined with predicting order requests, we established a multiobjective optimization model to solve the warehouse space allocation problem. First, we developed a model based on the NAR neural network to predict order requests. Subsequently, we used the improved NSGA-III based on good point set theory to construct a multiobjective optimization model to minimize resource loss, maximize efficiency in goods selection, and maximize goods accumulation. The following three modes were tested to allocate warehouse storage space: random, ABC, and prediction-oriented. Finally, using actual order data, we conducted a comparative analysis of the three modes regarding their efficiency in goods selection. The method proposed by this study improved goods selection efficiency by a sizable margin (23.8%). |
| format | Article |
| id | doaj-art-60a34bcb42b74fd2bde6c1262fcc3973 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-60a34bcb42b74fd2bde6c1262fcc39732025-02-03T06:12:13ZengWileyComplexity1099-05262022-01-01202210.1155/2022/4247290Establishing a Novel Algorithm for Highly Responsive Storage Space Allocation Based on NAR and Improved NSGA-IIIPeijian Wu0Yulu Chen1School of Business and AdministrationSchool of Business and AdministrationEstablishing a rapid-response mechanism to manage customer orders is very important in managing demand surges. In this study, combined with predicting order requests, we established a multiobjective optimization model to solve the warehouse space allocation problem. First, we developed a model based on the NAR neural network to predict order requests. Subsequently, we used the improved NSGA-III based on good point set theory to construct a multiobjective optimization model to minimize resource loss, maximize efficiency in goods selection, and maximize goods accumulation. The following three modes were tested to allocate warehouse storage space: random, ABC, and prediction-oriented. Finally, using actual order data, we conducted a comparative analysis of the three modes regarding their efficiency in goods selection. The method proposed by this study improved goods selection efficiency by a sizable margin (23.8%).http://dx.doi.org/10.1155/2022/4247290 |
| spellingShingle | Peijian Wu Yulu Chen Establishing a Novel Algorithm for Highly Responsive Storage Space Allocation Based on NAR and Improved NSGA-III Complexity |
| title | Establishing a Novel Algorithm for Highly Responsive Storage Space Allocation Based on NAR and Improved NSGA-III |
| title_full | Establishing a Novel Algorithm for Highly Responsive Storage Space Allocation Based on NAR and Improved NSGA-III |
| title_fullStr | Establishing a Novel Algorithm for Highly Responsive Storage Space Allocation Based on NAR and Improved NSGA-III |
| title_full_unstemmed | Establishing a Novel Algorithm for Highly Responsive Storage Space Allocation Based on NAR and Improved NSGA-III |
| title_short | Establishing a Novel Algorithm for Highly Responsive Storage Space Allocation Based on NAR and Improved NSGA-III |
| title_sort | establishing a novel algorithm for highly responsive storage space allocation based on nar and improved nsga iii |
| url | http://dx.doi.org/10.1155/2022/4247290 |
| work_keys_str_mv | AT peijianwu establishinganovelalgorithmforhighlyresponsivestoragespaceallocationbasedonnarandimprovednsgaiii AT yuluchen establishinganovelalgorithmforhighlyresponsivestoragespaceallocationbasedonnarandimprovednsgaiii |