An Effective Hybrid Algorithm Based on Particle Swarm Optimization with Migration Method for Solving the Multiskill Resource-Constrained Project Scheduling Problem. (15th February 2022)

• Record Type: Journal Article
• Authors: Dang Quoc, Huu; Nguyen The, Loc; Nguyen Doan, Cuong
• Other Names: Rathnayake Upaka Academic Editor.
• Is Part Of: Applied computational intelligence and soft computing. Volume 2022(2022)
• Publication Date: 2022-02-15
• Subjects: Computational intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• DOI: 10.1155/2022/6230145
• Languages: English
• ISSNs: 1687-9724

Abstract

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 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.