Multi skill project scheduling optimization based on quality transmission and rework network reconstruction DOI Creative Commons
Jie Peng, Zhuo Su, Xiao Liu

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 19, 2025

Quality deficiencies are widely acknowledged as a primary driver of project rework, with personnel skill levels serving critical determinant activity quality. This study presents scheduling model that integrates quality transmission mechanisms and dynamic rework subnet reconstruction within the Multi-Skill Resource-Constrained Project Scheduling Problem (MSRCPSP) framework. The proposed aims to optimize duration while mitigating risks. To address computational complexity model, an Improved Gazelle Optimization Algorithm (GOAIP) was developed, incorporating operators, shuffle crossover, Gaussian mutation strategies balance global local optimization. Experimental validation across diverse case scales demonstrates algorithm outperform mainstream optimization techniques in solution accuracy convergence efficiency, highlighting their robust applicability practical significance.

Language: Английский

An Innovative Differentiated Creative Search Based on Collaborative Development and Population Evaluation DOI Creative Commons
Xinyu Cai, Chaoyong Zhang

Biomimetics, Journal Year: 2025, Volume and Issue: 10(5), P. 260 - 260

Published: April 23, 2025

In real-world applications, many complex problems can be formulated as mathematical optimization challenges, and efficiently solving these is critical. Metaheuristic algorithms have proven highly effective in addressing a wide range of engineering issues. The differentiated creative search recently proposed evolution-based meta-heuristic algorithm with certain advantages. However, it also has limitations, including weakened population diversity, reduced efficiency, hindrance comprehensive exploration the solution space. To address shortcomings DCS algorithm, this paper proposes multi-strategy (MSDCS) based on collaborative development mechanism evaluation strategy. First, that organically integrates estimation distribution to compensate for algorithm’s insufficient ability its tendency fall into local optimums through guiding effect dominant populations, improve quality efficiency at same time. Secondly, new strategy realize coordinated transition between exploitation fitness distance. Finally, linear size reduction incorporated DCS, which significantly improves overall performance by maintaining large initial stage enhance capability extensive space, then gradually decreasing later capability. A series validations was conducted CEC2018 test set, experimental results were analyzed using Friedman Wilcoxon rank sum test. show superior MSDCS terms convergence speed, stability, global optimization. addition, successfully applied several constrained problems. all cases, outperforms basic fast strong robustness, emphasizing efficacy practical applications.

Language: Английский

Citations

0
Research on Crop Planting Strategies Based on Multi-Objective NSGA-III Optimization Algorithm and Robust Optimization DOI
Zhixiang Liu,

B. L. Wang,

Jing Zhou

et al.

Published: Jan. 10, 2025

Language: Английский

Citations

0
Multi skill project scheduling optimization based on quality transmission and rework network reconstruction DOI Creative Commons
Jie Peng, Zhuo Su, Xiao Liu

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 19, 2025

Quality deficiencies are widely acknowledged as a primary driver of project rework, with personnel skill levels serving critical determinant activity quality. This study presents scheduling model that integrates quality transmission mechanisms and dynamic rework subnet reconstruction within the Multi-Skill Resource-Constrained Project Scheduling Problem (MSRCPSP) framework. The proposed aims to optimize duration while mitigating risks. To address computational complexity model, an Improved Gazelle Optimization Algorithm (GOAIP) was developed, incorporating operators, shuffle crossover, Gaussian mutation strategies balance global local optimization. Experimental validation across diverse case scales demonstrates algorithm outperform mainstream optimization techniques in solution accuracy convergence efficiency, highlighting their robust applicability practical significance.

Language: Английский

Citations

0