Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has
gained prominence in the last two decades due to its ease of application in unsupervised …

Metaheuristic optimization algorithms have become popular choice for solving complex and
intricate problems which are otherwise difficult to solve by traditional methods. In the present …

Evolutionary computation has become an important problem solving methodology among
many researchers. The population-based collective learning process, selfadaptation, and …

Particle swarm optimisation (PSO) has been enormously successful. Within little more than a
decade hundreds of papers have reported successful applications of PSO. In fact, there are …

This paper presents a hybridization of particle swarm optimization (PSO) and artificial bee
colony (ABC) approaches, based on recombination procedure. The PSO and ABC are …

Wireless sensor networks (WSNs) are generically self-configuring and organizing networks
with constrained communicational ability and energy supply. One of the crucial crises in …

Fitting data points to curves (usually referred to as curve reconstruction) is a major issue in
computer-aided design/manufacturing (CAD/CAM). This problem appears recurrently in …

Meta-heuristic optimization algorithms have become popular choice for solving complex and
intricate problems which are otherwise difficult to solve by traditional methods. In the present …

In this paper a new class of hybridization strategies between GA and PSO is presented and
validated. The Genetical Swarm Optimization (GSO) approach is presented here with …

This paper proposes a new Direction Aware Particle Swarm Optimization algorithm with
Sensitive Swarm Leader (DAPSO-SSL). DAPSO-SSL maps the basic human nature of …