Modeling and IAHA Solution for Task Scheduling Problem of Processing Crowdsourcing in the Context of Social Manufacturing
The paper addresses the discrete characteristics of the processing crowdsourcing task scheduling problem in the context of social manufacturing, divides it into two subproblems of social manufacturing unit selecting and subtask sorting, establishes its mixed-integer programming with the objective of...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Systems |
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| Online Access: | https://www.mdpi.com/2079-8954/11/8/383 |
| _version_ | 1827728651980898304 |
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| author | Gaohong Zhu Dianting Liu |
| author_facet | Gaohong Zhu Dianting Liu |
| author_sort | Gaohong Zhu |
| collection | DOAJ |
| description | The paper addresses the discrete characteristics of the processing crowdsourcing task scheduling problem in the context of social manufacturing, divides it into two subproblems of social manufacturing unit selecting and subtask sorting, establishes its mixed-integer programming with the objective of minimizing the maximum completion time, and proposes an improved artificial hummingbird algorithm (IAHA) for solving it. The IAHA uses initialization rules of global selection, local selection, and random selection to improve the quality of the initial population, the Levy flight to improve guided foraging and territorial foraging, the simplex search strategy to improve migration foraging to enhance the merit-seeking ability, and the greedy decoding method to improve the quality of the solution and reduce solution time. For the IAHA, orthogonal tests are designed to obtain the optimal combination of parameters, and comparative tests are made with variants of the AHA and other algorithms on the benchmark case and a simulated crowdsourcing case. The experimental results show that the IAHA can obtain superior solutions in many cases with economy and effectiveness. |
| first_indexed | 2024-03-10T23:33:03Z |
| format | Article |
| id | doaj.art-d71b51dcdeec4c89b1eccfb98e4c031f |
| institution | Directory Open Access Journal |
| issn | 2079-8954 |
| language | English |
| last_indexed | 2024-03-10T23:33:03Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj.art-d71b51dcdeec4c89b1eccfb98e4c031f2023-11-19T03:12:24ZengMDPI AGSystems2079-89542023-07-0111838310.3390/systems11080383Modeling and IAHA Solution for Task Scheduling Problem of Processing Crowdsourcing in the Context of Social ManufacturingGaohong Zhu0Dianting Liu1Key Laboratory of Advanced Manufacturing and Automation Technology, Education Department of Guangxi Zhuang Autonomous Region, Guilin University of Technology, Guilin 541006, ChinaKey Laboratory of Advanced Manufacturing and Automation Technology, Education Department of Guangxi Zhuang Autonomous Region, Guilin University of Technology, Guilin 541006, ChinaThe paper addresses the discrete characteristics of the processing crowdsourcing task scheduling problem in the context of social manufacturing, divides it into two subproblems of social manufacturing unit selecting and subtask sorting, establishes its mixed-integer programming with the objective of minimizing the maximum completion time, and proposes an improved artificial hummingbird algorithm (IAHA) for solving it. The IAHA uses initialization rules of global selection, local selection, and random selection to improve the quality of the initial population, the Levy flight to improve guided foraging and territorial foraging, the simplex search strategy to improve migration foraging to enhance the merit-seeking ability, and the greedy decoding method to improve the quality of the solution and reduce solution time. For the IAHA, orthogonal tests are designed to obtain the optimal combination of parameters, and comparative tests are made with variants of the AHA and other algorithms on the benchmark case and a simulated crowdsourcing case. The experimental results show that the IAHA can obtain superior solutions in many cases with economy and effectiveness.https://www.mdpi.com/2079-8954/11/8/383social manufacturingcrowdsourced task schedulingflexible job shop schedulingartificial hummingbird algorithm |
| spellingShingle | Gaohong Zhu Dianting Liu Modeling and IAHA Solution for Task Scheduling Problem of Processing Crowdsourcing in the Context of Social Manufacturing Systems social manufacturing crowdsourced task scheduling flexible job shop scheduling artificial hummingbird algorithm |
| title | Modeling and IAHA Solution for Task Scheduling Problem of Processing Crowdsourcing in the Context of Social Manufacturing |
| title_full | Modeling and IAHA Solution for Task Scheduling Problem of Processing Crowdsourcing in the Context of Social Manufacturing |
| title_fullStr | Modeling and IAHA Solution for Task Scheduling Problem of Processing Crowdsourcing in the Context of Social Manufacturing |
| title_full_unstemmed | Modeling and IAHA Solution for Task Scheduling Problem of Processing Crowdsourcing in the Context of Social Manufacturing |
| title_short | Modeling and IAHA Solution for Task Scheduling Problem of Processing Crowdsourcing in the Context of Social Manufacturing |
| title_sort | modeling and iaha solution for task scheduling problem of processing crowdsourcing in the context of social manufacturing |
| topic | social manufacturing crowdsourced task scheduling flexible job shop scheduling artificial hummingbird algorithm |
| url | https://www.mdpi.com/2079-8954/11/8/383 |
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