Publication Date
Spring 2025
Degree Type
Master's Project
Degree Name
Master of Science in Computer Science (MSCS)
Department
Computer Science
First Advisor
Katerina Potika
Second Advisor
Robert Chun
Third Advisor
Gaurav Jadhav
Keywords
Permutation Flowshop Scheduling Problem, Makespan, Metaheuristics, Island Genetic Algorithm, Combinatorial Optimization.
Abstract
The Permutation Flowshop Scheduling Problem is a well-known NP-hard combinatorial optimization problem that involves the sequencing of n jobs across m machines in the same order to minimize the total makespan value. This project proposes a Heterogeneous Island Genetic Algorithm framework (HIGA). Each island represents a group of solutions that evolve in parallel using different initialization heuristics, crossover and mutation operators, and adaptive parameters. A dynamic, stagnation-based migration strategy is proposed to maintain targeted communication between the islands. The proposed HIGA approach was compared against the basic Standard Genetic Algorithm (SGA) and a more advanced Niche-based Genetic Algorithm (NEH-NGA) on Taillard’s benchmark dataset. Experimental results indicate HIGA effectively balances solution quality and efficiency, matching the best-known makespan value or coming close to it, particularly for larger instances, while being several-fold faster than NEH-NGA and achieving significantly better results than the SGA
Recommended Citation
Salim, Sahil, "Optimization of Permutation Flowshop Scheduling Using an Island Genetic Algorithm for Makespan Minimization" (2025). Master's Projects. 1536.
DOI: https://doi.org/10.31979/etd.hrp6-zyd4
https://scholarworks.sjsu.edu/etd_projects/1536
