An Effective Hybrid Algorithm Based on Particle Swarm Optimization with Migration Method for Solving the Multiskill Resource-Constrained Project Scheduling Problem
The paper proposed a new algorithm to solve the Multiskill Resource-Constrained Project Scheduling Problem (MS-RCPSP), a combinational optimization problem proved in NP-Hard classification, so it cannot get an optimal solution in polynomial time. The NP-Hard problems can be solved using metaheuristi...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Applied Computational Intelligence and Soft Computing |
| Online Access: | http://dx.doi.org/10.1155/2022/6230145 |
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| author | Huu Dang Quoc Loc Nguyen The Cuong Nguyen Doan |
| author_facet | Huu Dang Quoc Loc Nguyen The Cuong Nguyen Doan |
| author_sort | Huu Dang Quoc |
| collection | DOAJ |
| description | The paper proposed a new algorithm to solve the Multiskill Resource-Constrained Project Scheduling Problem (MS-RCPSP), a combinational optimization problem proved in NP-Hard classification, so it cannot get an optimal solution in polynomial time. The NP-Hard problems can be solved using metaheuristic methods to evolve the population over many generations, thereby finding approximate solutions. However, most metaheuristics have a weakness that can be dropping into local extreme after a number of evolution generations. The new algorithm proposed in this paper will resolve that by detecting local extremes and escaping that by moving the population to new space. That is executed using the Migration technique combined with the Particle Swarm Optimization (PSO) method. The new algorithm is called M-PSO. The experiments were conducted with the iMOPSE benchmark dataset and showed that the M-PSO was more practical than the early algorithms. |
| format | Article |
| id | doaj-art-4be419abf1d3406b8885b76cc2f96641 |
| institution | Kabale University |
| issn | 1687-9732 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Computational Intelligence and Soft Computing |
| spelling | doaj-art-4be419abf1d3406b8885b76cc2f966412025-02-03T01:11:56ZengWileyApplied Computational Intelligence and Soft Computing1687-97322022-01-01202210.1155/2022/6230145An Effective Hybrid Algorithm Based on Particle Swarm Optimization with Migration Method for Solving the Multiskill Resource-Constrained Project Scheduling ProblemHuu Dang Quoc0Loc Nguyen The1Cuong Nguyen Doan2Thuong Mai UniversityHa Noi National University of EducationMilitary Institute of Science and TechnologyThe paper proposed a new algorithm to solve the Multiskill Resource-Constrained Project Scheduling Problem (MS-RCPSP), a combinational optimization problem proved in NP-Hard classification, so it cannot get an optimal solution in polynomial time. The NP-Hard problems can be solved using metaheuristic methods to evolve the population over many generations, thereby finding approximate solutions. However, most metaheuristics have a weakness that can be dropping into local extreme after a number of evolution generations. The new algorithm proposed in this paper will resolve that by detecting local extremes and escaping that by moving the population to new space. That is executed using the Migration technique combined with the Particle Swarm Optimization (PSO) method. The new algorithm is called M-PSO. The experiments were conducted with the iMOPSE benchmark dataset and showed that the M-PSO was more practical than the early algorithms.http://dx.doi.org/10.1155/2022/6230145 |
| spellingShingle | Huu Dang Quoc Loc Nguyen The Cuong Nguyen Doan An Effective Hybrid Algorithm Based on Particle Swarm Optimization with Migration Method for Solving the Multiskill Resource-Constrained Project Scheduling Problem Applied Computational Intelligence and Soft Computing |
| title | An Effective Hybrid Algorithm Based on Particle Swarm Optimization with Migration Method for Solving the Multiskill Resource-Constrained Project Scheduling Problem |
| title_full | An Effective Hybrid Algorithm Based on Particle Swarm Optimization with Migration Method for Solving the Multiskill Resource-Constrained Project Scheduling Problem |
| title_fullStr | An Effective Hybrid Algorithm Based on Particle Swarm Optimization with Migration Method for Solving the Multiskill Resource-Constrained Project Scheduling Problem |
| title_full_unstemmed | An Effective Hybrid Algorithm Based on Particle Swarm Optimization with Migration Method for Solving the Multiskill Resource-Constrained Project Scheduling Problem |
| title_short | An Effective Hybrid Algorithm Based on Particle Swarm Optimization with Migration Method for Solving the Multiskill Resource-Constrained Project Scheduling Problem |
| title_sort | effective hybrid algorithm based on particle swarm optimization with migration method for solving the multiskill resource constrained project scheduling problem |
| url | http://dx.doi.org/10.1155/2022/6230145 |
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