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

Computing equilibria of multiplayer noncooperative normal form games is a difficult computational task. In games having more equilibria mathematical algorithms are not capable to detect all equilibria at a time. Evolutionary algorithms are powerful search tools for solving difficult optimization problems. It is shown how an evolutionary algorithm designed for multimodal optimization can be used...

Metaheuristic algorithms are widely used for optimization in both research and the industrial community simplicity, flexibility, robustness. However, multi-modal is a difficult task, even metaheuristic algorithms. Two important issues that need to be handled solving problems (a) categorize multiple local/global optima (b) uphold these till ending. Besides, robust local search ability also prere...

A new evolutionary algorithm for the global optimization of multimodal functions is presented. The algorithm is essentially a parallel direct search method which maintains a populations of individuals and utilizes an evolution operator to evolve them. This operator has two functions. Firstly, to exploit the search space as much as possible, and secondly to form an improved population for the ne...

This paper deals with the dynamic optimization of a wastewater treatment plant model for nitrogen removal. Two process variables (i.e., aeration factor in a tank and internal recycle flow rate) are selected as control variables and their time profiles are approximated using the control vector parameterization (CVP) technique. Two conflicting objectives have been considered to formulate a multio...

In this paper, an improved multimodal optimization (MMO) algorithm,calledLSEPSO,has been proposed. LSEPSO combinedElectrostatic Particle Swarm Optimization (EPSO) algorithm and a local search method and then madesome modification onthem. It has been shown to improve global and local optima finding ability of the algorithm. This algorithm useda modified local search to improve particle's persona...