Search Results - (( using (evolutionary OR evolution) path algorithm ) OR ( basic optimization search algorithm ))
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The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment
Published 2016“…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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Basic firefly algorithm for document clustering
Published 2015“…To address the shortcoming, this paper proposes a Basic Firefly (Basic FA) algorithm to cluster text documents.The algorithm employs the Average Distance to Document Centroid (ADDC) as the objective function of the search. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm
Published 2016“…Basically, Cuckoo searching algorithm imitates the natural evolution of a population with initial solutions. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…In future, this work could be enhanced for better performances in both aspects using another variant of the PSO or other potential metaheuristic searching techniques such as Firefly Optimization, Bat Algorithm and etc.…”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
Published 2023Conference Paper -
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Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim
Published 2007“…In this paper, GA has been applied to find the minimum path, then result will be compared with Dijkstra's algorithm are presented.…”
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Mathematical formulation of tabu search in combinatorial optimization
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Particle swarm optimization (PSO) for CNC route problem
Published 2002“…The algorithm used in this project is the Global Best (gbest) algorithm where it is a basic algorithm of Particle Swarm Optimization which applicable the shortest time and path of CNC machine to complete the process of drilling. …”
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Undergraduates Project Papers -
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Particle Swarm Optimization algorithm for facial emotion detection
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Tackling the berth allocation problem via harmony search algorithm
Published 2024“…Harmony Search Algorithm (HSA) is one of the recent population-based optimization methods which inspired by modern-nature. …”
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The design and applications of the african buffalo algorithm for general optimization problems
Published 2017“…Optimization, basically, is the economics of science. …”
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Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators
Published 2024“…Interestingly, the manipulator's behaviours using the spiral dynamics algorithm for PID controller tuning were superior to those using alternative methods. …”
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Local search manoeuvres recruitment in the bees algorithm
Published 2011“…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources.During the searching, the original BA ignores the possibilities of the recruits being lost during the flying.The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon.This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor.The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction.The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions.The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.…”
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