The objective of this thesis is to investigate how to improve Particle Swarm Optimization by hybridization of stochastic search heuristics and by a Self-Organized Criticality extension. The thesis will describe two hybrid models extending Particle Swarm Optimization with two aspects from Evolutionary Algorithms, recombination via breeding and gene flow restriction via subpopulations. A further ...

The rational economic load dispatch can not only save the energy, but also improve efficiency of power systems. Therefore it is important to research economic load dispatch problem. However, The problem is a complex and nonlinear optimization problem considering valve-point loading effects of generating units; it is difficult to solve the problem using traditional optimization method. Therefore...

Adaptability to various driving conditions (TCs) is one of the essential indicators assess optimality power management strategies (PMSs) plug-in hybrid electric vehicles (PHEVs). In this study, a novel optimal PMS with improved adaptability TCs proposed for PHEVs achieve energy-efficient control in momentary scenarios by virtue advanced internet (IoVs), thus contributing remarkable promotion fu...

The home healthcare staff scheduling problem is concerned with the allocation of care tasks to healthcare staff at a minimal cost, subject to healthcare service requirements, labor law, organizational requirements, staff preferences, and other restrictions. Healthcare service providers strive to meet the time window restrictions specified by the patients to improve their service quality. This p...

This paper proposes a new support vector machine (SVM) optimization scheme based on an improved chaotic fly optimization algorithm (FOA) with a mutation strategy to simultaneously perform parameter setting turning for the SVM and feature selection. In the improved FOA, the chaotic particle initializes the fruit fly swarm location and replaces the expression of distance for the fruit fly to find...

In this study, a new hybrid metaheuristic algorithm named Chaotic Sand Cat Swarm Optimization (CSCSO) is proposed for constrained and complex optimization problems. This combines the features of recently introduced SCSO with concept chaos. The basic aim to integrate chaos feature non-recurring locations into SCSO’s core search process improve global performance convergence behavior. Thus, rando...

In light of the accuracy of particle swarm optimization-particle filter (PSO-PF) inadequate for multi-robot cooperative positioning, the paper presents population density particle swarm optimization-particle filter (PDPSO-PF), which draws cooperative coevolutionary algorithm in ecology into particle swarm optimization. By taking full account of the competitive relationship between the environme...

In this paper, an optimal redundant instrumentation sensor network design methodology is presented for complex chemical process plants using a combinatorial particle swarm optimization search (CPSO) engine. The approach, which is more flexible and general in comparison with previous works, aims to minimize cost as a main design factor, similar to the usual trend in the literature. Besides, it c...