A Novel Maximin-Based Multi-Objective Evolutionary Algorithm Using One-by-One Update Scheme for Multi-Robot Scheduling Optimization
With the continuous development of E-commerce, warehouse logistics is also facing emerging challenges, including more batches of orders and shorter order processing cycles. When more orders need to be processed simultaneously, some existing task scheduling methods may not be able to give a suitable...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9514575/ |
| _version_ | 1818608893173956608 |
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| author | Shujun Yang Yichuan Zhang Lianbo Ma Yan Song Ping Zhou Gang Shi Hanning Chen |
| author_facet | Shujun Yang Yichuan Zhang Lianbo Ma Yan Song Ping Zhou Gang Shi Hanning Chen |
| author_sort | Shujun Yang |
| collection | DOAJ |
| description | With the continuous development of E-commerce, warehouse logistics is also facing emerging challenges, including more batches of orders and shorter order processing cycles. When more orders need to be processed simultaneously, some existing task scheduling methods may not be able to give a suitable plan, which delays order processing and reduces the efficiency of the warehouse. Therefore, the intelligent warehouse system that uses autonomous robots for automated storage and intelligent order scheduling is becoming mainstream. Based on this concept, we propose a multi-robot cooperative scheduling system in the intelligent warehouse. The aim of the multi-robot cooperative scheduling system of the intelligent storage is to drive many robots in an intelligent warehouse to perform the distributed tasks in an optimal (e.g., time-saving and energy-conserved) way. In this paper, we propose a multi-robot cooperative task scheduling model in the intelligent warehouse. For this model, we design a maximin-based multi-objective algorithm, which uses a one-by-one update scheme to select individuals. In this algorithm, two indicators are devised to discriminate the equivalent individuals with the same maximin fitness value in the environmental selection process. The results on benchmark test suite show that our algorithm is indeed a useful optimizer. Then it is applied to settle the multi-robot scheduling problem in the intelligence warehouse. Simulation experiment results demonstrate the efficiency of the proposed algorithm on the real-world scheduling problem. |
| first_indexed | 2024-12-16T14:49:52Z |
| format | Article |
| id | doaj.art-84f88f567c8249c09a584f3da9178d57 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T14:49:52Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-84f88f567c8249c09a584f3da9178d572022-12-21T22:27:38ZengIEEEIEEE Access2169-35362021-01-01912131612132810.1109/ACCESS.2021.31051029514575A Novel Maximin-Based Multi-Objective Evolutionary Algorithm Using One-by-One Update Scheme for Multi-Robot Scheduling OptimizationShujun Yang0https://orcid.org/0000-0002-9020-7456Yichuan Zhang1Lianbo Ma2https://orcid.org/0000-0002-9969-211XYan Song3Ping Zhou4https://orcid.org/0000-0001-6312-2601Gang Shi5Hanning Chen6Software College, Northeastern University, Shenyang, ChinaSoftware College, Northeastern University, Shenyang, ChinaSoftware College, Northeastern University, Shenyang, ChinaSchool of Physics, Liaoning University, Shenyang, ChinaSoftware College, Northeastern University, Shenyang, ChinaChinese Academy of Sciences, Shenyang Institute of Automation, Shenyang, ChinaSchool of Computer Science and Technology, Tiangong University, Tianjin, ChinaWith the continuous development of E-commerce, warehouse logistics is also facing emerging challenges, including more batches of orders and shorter order processing cycles. When more orders need to be processed simultaneously, some existing task scheduling methods may not be able to give a suitable plan, which delays order processing and reduces the efficiency of the warehouse. Therefore, the intelligent warehouse system that uses autonomous robots for automated storage and intelligent order scheduling is becoming mainstream. Based on this concept, we propose a multi-robot cooperative scheduling system in the intelligent warehouse. The aim of the multi-robot cooperative scheduling system of the intelligent storage is to drive many robots in an intelligent warehouse to perform the distributed tasks in an optimal (e.g., time-saving and energy-conserved) way. In this paper, we propose a multi-robot cooperative task scheduling model in the intelligent warehouse. For this model, we design a maximin-based multi-objective algorithm, which uses a one-by-one update scheme to select individuals. In this algorithm, two indicators are devised to discriminate the equivalent individuals with the same maximin fitness value in the environmental selection process. The results on benchmark test suite show that our algorithm is indeed a useful optimizer. Then it is applied to settle the multi-robot scheduling problem in the intelligence warehouse. Simulation experiment results demonstrate the efficiency of the proposed algorithm on the real-world scheduling problem.https://ieeexplore.ieee.org/document/9514575/Many-objective optimizationmulti-objective optimizationmaximin fitness functionone-by-one update schememulti-robot scheduling optimization |
| spellingShingle | Shujun Yang Yichuan Zhang Lianbo Ma Yan Song Ping Zhou Gang Shi Hanning Chen A Novel Maximin-Based Multi-Objective Evolutionary Algorithm Using One-by-One Update Scheme for Multi-Robot Scheduling Optimization IEEE Access Many-objective optimization multi-objective optimization maximin fitness function one-by-one update scheme multi-robot scheduling optimization |
| title | A Novel Maximin-Based Multi-Objective Evolutionary Algorithm Using One-by-One Update Scheme for Multi-Robot Scheduling Optimization |
| title_full | A Novel Maximin-Based Multi-Objective Evolutionary Algorithm Using One-by-One Update Scheme for Multi-Robot Scheduling Optimization |
| title_fullStr | A Novel Maximin-Based Multi-Objective Evolutionary Algorithm Using One-by-One Update Scheme for Multi-Robot Scheduling Optimization |
| title_full_unstemmed | A Novel Maximin-Based Multi-Objective Evolutionary Algorithm Using One-by-One Update Scheme for Multi-Robot Scheduling Optimization |
| title_short | A Novel Maximin-Based Multi-Objective Evolutionary Algorithm Using One-by-One Update Scheme for Multi-Robot Scheduling Optimization |
| title_sort | novel maximin based multi objective evolutionary algorithm using one by one update scheme for multi robot scheduling optimization |
| topic | Many-objective optimization multi-objective optimization maximin fitness function one-by-one update scheme multi-robot scheduling optimization |
| url | https://ieeexplore.ieee.org/document/9514575/ |
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