This paper presents a novel explicit exploration information exchange mechanism for niche technique. In this framework, the whole population is divided into many sub-populations. The different sub-population communicates with each other. One sub-population exploration area does not be explored by others. Based on this framework, a multi-sub-swarm particle swarm optimization (MSSPSO) algorithm i...

This paper examines the effects of local search on hybrid genetic algorithm performance and population sizing. It compares the performance of a self-adaptive hybrid genetic algorithm (SAHGA) to a non-adaptive hybrid genetic algorithm (NAHGA) and the simple genetic algorithm (SGA) on eight different test functions, including unimodal, multimodal and constrained optimization problems. The results...

Many signal processing applications pose optimization problems with multimodal and nonsmooth cost functions. Gradient methods are ine!ective in these situations. The adaptive simulated annealing (ASA) o!ers a viable optimization tool for tackling these di$cult nonlinear optimization problems. Three applications, maximum likelihood (ML) joint channel and data estimation, in"nite-impulse-response...

Artificial bee colony (ABC) algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA), artificial colony optimization (ACO), and particle swarm optimization (PSO). However, the ABC still has some limitations. For example, ABC can easily get trapped ...

This paper introduce one innovations into the world of multimodal function optimization: a new Cultural Algorithm (CA) based on Genetic Algorithm (GA) with a new adaptive mutation (AM-CGA). The idea is to use knowledge about local optima found during the search with other techniques utilized for escape from local minimum in multimodal functions. The search knowledge was maintained using a Cultu...

Image segmentation of pulmonary parenchyma can be detected from multisliced CT images using image segmentation. It can be modeled as a nonlinear multimodal global optimization problem. The traditional 2D Otsu algorithm, though effective, is quite time consuming for determining the optimum threshold values. In this paper we propose a combination of 2D Otsu method with modified ABC algorithm (cal...

This study introduces the Borg multi-objective evolutionary algorithm (MOEA) for many-objective, multimodal optimization. The Borg MOEA combines ε-dominance, a measure of convergence speed named ε-progress, randomized restarts, and auto-adaptive multioperator recombination into a unified optimization framework. A comparative study on 33 instances of 18 test problems from the DTLZ, WFG, and CEC ...

This paper proposes a novel adaptive sequential niche particle swarm optimization (ASNPSO) algorithm, which uses multiple subswarms to detect optimal solutions sequentially. In this algorithm, the hill valley function is used to determine how to change the fitness of a particle in a sub-swarm run currently. This algorithm has strong and adaptive searching ability. The experimental results show ...

This article presents the development of an adaptive multimodal Digital Talking Book player using FAME. FAME is a conceptual framework for the development of adaptive multimodal applications. FAME's adaptation is based on context changes. The context is defined by three entities: User, Platform and Environment. The adaptation can impact multimodal operations, as well as interaction and presenta...