Genetic Algorithm for Multi-objective Optimization Using GDEA

• Published in: Advances in Natural Computation pp. 409 - 416
• Main Authors: Yun, Yeboon, Yoon, Min, Nakayama, Hirotaka
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2005; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Artificial intelligence; Computer science; control theory; systems; Exact sciences and technology; Data analysis; Pareto optimum; Genetic algorithm; Optimal solution; Multiobjective programming; Optimization; Mathematical programming

Recently, many genetic algorithms (GAs) have been developed as an approximate method to generate Pareto frontier (the set of Pareto optimal solutions) to multi-objective optimization problem. In multi-objective GAs, there are two important problems : how to assign a fitness for each individual, and...