2022
DOI: 10.1155/2022/6230145
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An Effective Hybrid Algorithm Based on Particle Swarm Optimization with Migration Method for Solving the Multiskill Resource-Constrained Project Scheduling Problem

Abstract: 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 gener… Show more

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Cited by 5 publications
(3 citation statements)
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References 27 publications
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“…The best particle is the best result (expressing the value of the fitness function) that has been achieved so far. The objective function (F) is determined by the best position for each p, along with the p with the best position in the current set (Liu et al, 2016;Bharath et al, 2022;Moh et al, 2022;Mercangöz, 2021;Quoc et al, 2022;Ali and Tawhid, 2017;Saber et al, 2021).…”
Section: Preliminaries and Methodsmentioning
confidence: 99%
“…The best particle is the best result (expressing the value of the fitness function) that has been achieved so far. The objective function (F) is determined by the best position for each p, along with the p with the best position in the current set (Liu et al, 2016;Bharath et al, 2022;Moh et al, 2022;Mercangöz, 2021;Quoc et al, 2022;Ali and Tawhid, 2017;Saber et al, 2021).…”
Section: Preliminaries and Methodsmentioning
confidence: 99%
“…These EA algorithms contribute to the early-stage development of an optimal schedule, benefiting project management endeavors. Dang et al [27] present M-PSO, a novel particle swarm optimization technique. To enhance exploration, the algorithm incorporates a migration method to escape local optima and broaden the search space.…”
Section: Related Workmentioning
confidence: 99%
“…Reference 20 suggests a new algorithm to overcome the drawback of sliding into local extremes by combining the Migration method with the standard PSO. The suggested strategy finds local extremes in population evolution and suggests a fresh way to avoid them by migrating the population to a new values space.…”
Section: Related Studiesmentioning
confidence: 99%