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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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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim
Published 2021“…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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Hybrid artificial bee colony algorithm with branch and bound for two–sided assembly line balancing
Published 2018“…The branch and bound concept was applied by using mated workstations to overcome the slow convergence of the ABC algorithm and solve the problem optimality. The visual basic application software was used to generate different solutions with the various partial fitness of the proposed approach. …”
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Optimization of supply chain management by simulation based RFID with XBEE Network
Published 2015“…In order to solve this problem, a simulation based “Multi-Colony Global Particle Swarm Optimization (MC-GPSO)” algorithm was developed. This algorithm computes the optimal results of objective functions in a scientific manner. …”
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Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches
Published 2015“…The main objective of this research is to develop a computer program with capability of manipulating the onlooker bee approaches in ABC Algorithm for solving flowshop scheduling problem. …”
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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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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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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Data Analysis using Particle Swarm Optimization Algorithm
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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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Genetic algorithm optimization for coefficient of FFT processor
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Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators
Published 2023Subjects:Conference paper -
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Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application
Published 2024“…In this study, Ant Colony Optimization (ACO) algorithm is employed to find the best coalition of agents. …”
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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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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem
Published 2023“…This algorithm synergizes the ABC algorithm and Artificial Rabbits Optimization (ARO) algorithm. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…Significant modifications to the basic Jaya algorithm are done to create a modified Jaya (MJaya) algorithm that can handle the MOOPF problem. …”
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Convergence Analysis of the African Buffalo Optimization Algorithm
Published 2016“…The analysis of the convergence of Nature-inspired optimization algorithms is necessary to help researchers and practitioners understand the workings of the algorithms in the algorithms’ attempts at solutions. …”
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