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Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management
Published 2017“…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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Modelling of flexible beam based on ant colony optimization and cuckoo search algorithms
Published 2021“…Currently, there are plenty of methods that have been developed by researchers to suppress undesired vibration. Based on previous studies, most researchers nowadays use system identification (SI) as a modelling technique to develop a dynamic model of flexible structure via swarm intelligence algorithm (SIA). …”
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Plant leaf recognition algorithm using ant colony-based feature extraction technique
Published 2013“…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION
Published 2023“…The Bat Algorithm is a population-based meta-heuristic algorithm for solving continuous optimization problems. …”
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A new variable strength t-way strategy based on the cuckoo search algorithm
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Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing
Published 2011“…Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. …”
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A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network
Published 2023“…An enhanced genetic algorithm (EGA) is employed here to find the best possible path for data transmission which leads to meeting the QoF. …”
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A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network
Published 2023“…An enhanced genetic algorithm (EGA) is employed here to find the best possible path for data transmission which leads to meeting the QoF. …”
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A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network
Published 2023“…An enhanced genetic algorithm (EGA) is employed here to find the best possible path for data transmission which leads to meeting the QoF. …”
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DNA sequence design for direct-proportional length-based DNA computing: Particle swarm optimization vs population based ant colony optimization
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A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network
Published 2023“…An enhanced genetic algorithm (EGA) is employed here to find the best possible path for data transmission which leads to meeting the QoF. …”
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A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network
Published 2023“…An enhanced genetic algorithm (EGA) is employed here to find the best possible path for data transmission which leads to meeting the QoF. …”
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A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network
Published 2023“…An enhanced genetic algorithm (EGA) is employed here to find the best possible path for data transmission which leads to meeting the QoF. …”
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Solving the optimal reactive power dispatch problem based on moth-flame optimizer for power system operation and planning
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