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We introduce in this paper a new multi-objective memetic algorithm. This algorithm is a result of hybridization of the NSGA-II algorithm with a new designed local search procedure that we named Pareto Hill Climbing. Verification of our novel algorithm is carried out by testing it on two sets of multi-objective test problems and comparing it to other multi-objective evolutionary algorithms (MOEAs)...
This paper presents a new distributed differential evolution (dDE) algorithm and evaluates it according to the standard procedure set in the special session of continuous optimization of CECpsila05. We statistically validate our results in continuous optimization versus several other efficient techniques. Our distributed differential evolution is simple and accurate, at the same time amenable, to...
Since the estimation of distribution algorithms (EDAs) have been introduced, several single model based EDAs and mixture model based EDAs have been developed. Take Gaussian models as an example, EDAs based on single Gaussian distribution have good performance on solving simple unimodal functions and multimodal functions whose landscape has an obvious trend towards the global optimum. But they have...
Shuffled frog leaping (SFL) is a population based, cooperative search metaphor inspired by natural memetics. Its ability of adapting to dynamic environment makes SFL become one of the most important memetic algorithms. In order to improve the algorithmpsilas stability and the ability to search the global optimum, a novel dasiacognition componentpsila is introduced to enhance the effectiveness of the...
Ant Colony Algorithm is a very good combination optimization method from mimic the swarm intelligence of ant colony behaviours. To extend the traditional Ant Colony Algorithm to continuous optimization problems, from the connections of continuous optimization and searching process of Ant Colony Algorithm, here one new Continuous Ant Colony Algorithm is proposed. To verify the new algorithm, the typical...
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