Genetic Algorithm (GA) is known as a potent multiobjective optimization method, and the effectiveness of hybridizing it with local search (LS) has recently been reported in the li...
The paper presents a new genetic local search algorithm for multi-objective combinatorial optimization. The goal of the algorithm is to generate in a short time a set of approxima...
Although multi-objective GA (MOGA) is an efficient multiobjective optimization (MOO) method, it has some limitations that need to be tackled, which include unguaranteed uniformity...
Ken Harada, Jun Sakuma, Shigenobu Kobayashi, Isao ...
This paper is concerned with a specific brand of evolutionary algorithms: Memetic algorithms. A new local search technique with an adaptive neighborhood setting process is introdu...
Multiobjective optimization problems with many local Pareto fronts is a big challenge to evolutionary algorithms. In this paper, two operators, biased initialization and biased cr...
Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard Sen...