A Study on Multi-Objective Unrelated Parallel Machine Scheduling Using an Improved Spider Monkey Optimization Algorithm
Year: 2025
Type: conference-paper
Abstract: For the unrelated parallel machine scheduling problem, an improved Spider Monkey Optimization algorithm incorporating a variable neighborhood search (VNS) mechanism (VNS-SMO) is proposed to minimize the makespan, total tardiness, and total energy consumption. The VNS-SMO incorporates six types of neighborhood searches based on the objective characteristics to strengthen the optimization performance of the algorithm. To verify the effectiveness and superiority of VNS-SMO, first, Taguchi experiments were used to determine the algorithm parameters, and then three instances of different scales were solved and compared with the traditional algorithms NSGA-II, PSO, and SMO. The experimental results indicate that VNS-SMO significantly outperforms the comparison algorithms on IGD, NR, and C-matrix metrics, fully demonstrating its comprehensive advantages in convergence, distribution, and diversity.
Authors: Ziyang Ji, Yarong Chen, Lixuan Pan, Mudassar Rauf
Institution: Wenzhou University
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4415412453