This paper introduces a new technique called adaptive elitistpopulation search method for allowing unimodal function optimization methods to be extended to efficiently locate all optima of multimodal problems. The technique is based on the concept of adaptively adjusting the population size according to the individuals’ dissimilarity and the novel elitist genetic operators. Incorporation of the...

due to the fact that the error surface of adaptive infinite impulse response (iir) systems is generally nonlinear and multimodal, the conventional derivative based techniques fail when used in adaptive identification of such systems. in this case, global optimization techniques are required in order to avoid the local minima. harmony search (hs), a musical inspired metaheuristic, is a recently ...

Due to the fact that the error surface of adaptive infinite impulse response (IIR) systems is generally nonlinear and multimodal, the conventional derivative based techniques fail when used in adaptive identification of such systems. In this case, global optimization techniques are required in order to avoid the local minima. Harmony search (HS), a musical inspired metaheuristic, is a recently ...

In the last decades, many efforts have been made to solve multimodal optimization problems using Particle Swarm Optimization (PSO). To produce good results, these PSO algorithms need to specify some niching parameters to define the local neighborhood. In this paper, our motivation is to propose the novel neighborhood structures that remove undesirable niching parameters without sacrificing perf...

Many scientific and engineering applications involve finding more than one optimum. A comprehensive review of the existing works done in the field of multimodal function optimization was given and a critical analysis of the existing methods was also provided. Several techniques in solving multimodal function optimization problems were introduced, such as clearing, deterministic crowding, sharin...

The Generalized Generation Gap (G3) algorithm is one of the most efficient and effective state-of-the-art realcoded genetic algorithms (RCGAs) for unconstrained global optimization. However, its performance on multimodal optimization problems is known to be poor compared to unimodal optimization problems. The G3 algorithm currently relies on crossover operations only. The objective of this pape...

This paper introduces a new hybrid algorithm for locating all solutions in multimodal optimization problems. This algorithm combines an adaptive sequential niche techniquewith deterministic local optimization to detect all extrema efficiently and reliably. A genetic element of the hybrid algorithm performs W vailable online 9 March 2009

When Genetic Algorithms are employed in multimodal function optimization, identifying multiple peaks and maintaining subpopulations of the search space are two central themes. In this paper, we use an immune system model to explore the role of crossover in GAs with respect to these two issues. The experimental results reported here will shed more light into how crossover affects the GA’s search...

This paper introduces the application of particle swarm optimization techniques to generalized adaptive nonlinear and reeursive fdter structures. Particle swarm optimization (PSO) is a population based optimization algorithm, similar to the genetic algorithm (GA), that performs a struetored randomized search of an unknown parameter space by manipulating a population of parameter estimates to co...