Multi-objective Optimization of Supply Chain Problem Based NSGA-II-Cuckoo Search Algorithm

2018 2nd International Conference on Artificial Intelligence Applications and Technologies

计算机科学

Metiaf, Ali^1 ; Elkazzaz, Fathy^2 ; Qian Hong, Wu^1 ; Abozied, Mohammed^3

Beihang University, School of Electronics and Information Engineering, 100191, China^1

Benha University, Computer Science Department, Benha, Egypt^2

MTC, Electrical Engineering Department, Cairo, Egypt^3

关键词: Cuckoo algorithms;    Cuckoo search algorithms;    Initial population;    Multi objective;    Nondominated solutions;    NSGA-II algorithm;    Problem-based;    Stability and robustness;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/435/1/012030/pdf
DOI  :  10.1088/1757-899X/435/1/012030

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

A hybrid Cuckoo search algorithm and NSGA-II algorithm called NSGA-II-Cuckoo is proposed and applied to find a set of non-dominated solutions for multi-objective supply chain problem. In NSGA-II-Cuckoo, the cuckoo search algorithm is applied to generate the initial population that considers as a good start for another algorithm to reduce the time, avoids the local optima entrapment so its effect on the accuracy of the final solutions obtained by the NSGA-II algorithm. The presented results clarify the enhanced performance for the NSGA-II-Cuckoo algorithm, which provides a sufficient stability and robustness for solving multi-objective supply chain problem.