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1
Enhancement of Ant System Algorithm for Course Timetabling Problem
Published 2009“…This research starts with developing an algorithm based on original concept of Ant System Algorithm. …”
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2
A Comparative Performance Analysis of Gaussian Distribution Functions in Ant Swarm Optimized Rough Reducts
Published 2011“…Coexistence, cooperation, and individual contribution to food searching by a particle (ant) as a swarm (ant) survival behavior, depict the common characteristics of both algorithms. …”
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3
Application of Moth-Flame Optimizer and Ant Lion Optimizer to Solve Optimal Reactive Power Dispatch Problems
Published 2018“…MFO is developed by the inspiration of the natural navigation method of moths during night time while ALO is inspired by the natural foraging technique of antlions in hunting ants. These two algorithms are implemented in ORPD to determine the optimal value of generator buses voltage, transformers tap setting and reactive compensators sizing in order to minimize power loss in the transmission system. …”
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Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing
Published 2015“…One of the prominent intelligent algorithms is ant colony system (ACS) which is implemented widely to solve various types of scheduling problems. …”
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5
Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa
Published 2017“…The study of traditional marble game will be implemented in a game prototype using Ant Colony Optimization (ACO). …”
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6
Completion of contingency ranking selection (N-1) using ant colony optimization algorithm on 500 kV JAMALI system
Published 2022“…The ACO algorithm was implemented in this study through the initial parameter initialization stages, the probability value calculation stage, and the 0/1 knapsack problem calculation stage using the maximum cost function. …”
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7
A Hybrid ant colony optimization algorithm for solving a highly constrained nurse rostering problem
Published 2019“…Hence, this study focused on solving those issues arising in nurse rostering problems (NRPs) strategizing on a hybrid of Ant Colony Optimization (ACO) algorithm with a hill climbing technique. …”
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Modified ant colony optimization algorithms for deterministic and stochastic inventory routing problems / Lily Wong
Published 2018“…In addition, a new formulation for customer’s inventory pheromones is proposed and the selection of inventory updating mechanism is based on these pheromone values. The computational results show that the algorithms which implement this new formulation are able to produce better solutions. …”
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9
Analysis of Dijkstra’s and A* algorithm to find the shortest path
Published 2015“…There are so many algorithms used to find the shortest path such as Dijkstra, A* algorithm, Genetic algorithm, Floyd algorithm and Ant algorithm. …”
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10
Effectiveness of Nature-Inspired Algorithms using ANFIS for Blade Design Optimization and Wind Turbine Efficiency
Published 2019“…In this paper, nature-inspired algorithms, e.g., ant colony optimization (ACO), artificial bee colony (ABC), and particle swarm optimization (PSO) are used to search for the blade parameters that can give the maximum value of Cp for HAWT. …”
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Effectiveness of nature-inspired algorithms using ANFIS for blade design optimization and wind turbine efficiency
Published 2019“…In this paper, nature-inspired algorithms, e.g., ant colony optimization (ACO), artificial bee colony (ABC), and particle swarm optimization (PSO) are used to search for the blade parameters that can give the maximum value of Cp for HAWT. …”
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Computational intellegence approach for overcurrent relay coordination
Published 2024text::Final Year Project -
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Optimal overcurrent relay solutions for protection coordination using metaheuristics approaches with penalty function method
Published 2024“…This paper presents the development of overcurrent relay coordination (OCRC) problem formulation by implementing five well known metaheuristic algorithms that are Ant Lion Optimizer (ALO), Moth Flame Optimizer (MFO), Grey Wolf Optimizer (GWO), Particles Swarm Optimizer (PSO) and Barnacles Matting Optimizer (BMO). …”
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14
Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…In this research, the empirical experiments have been conducted for the five selected algorithms in the engineering optimization discipline, namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Ant Colony Optimization (ACO) and Artificial Immune System (AIS). …”
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15
Ant colony optimization and genetic algorithm models for suspended sediment discharge estimation for gorgan-river, Iran
Published 2011“…New models based on artificial intelligence models, namely; Ant Colony Optimization (ACO) and Genetic Algorithm (GA) are now being used more frequently to solve optimization problems. …”
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16
Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…In fact, the design of eFPA adds new value into the domain software testing as it is the first t-way strategy that adopts elitism-FPA as its core implementation.…”
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17
Machine-learning guided fracture density seismic inversion: A new approach in fractured basement characterisation
Published 2020“…It allows potential fracture density mapping by using geobody analysis through classification or cut off value. The novelty of the study is presented based on the potential to generate a 3D volume of well log calibrated fracture density by empowering the seismic elastic inversion with a sophisticated machine learning algorithm. …”
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Solving large-scale problems using multi-swarm particle swarm approach
Published 2018“…The proposed approach strived to scale up the application of the (PSO) algorithm towards solving large-scale optimization tasks of up to 1000 real-valued variables. …”
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Trust-based enhanced ACO algorithm for secure routing in IoT
Published 2024“…The trust evaluation system has been enhanced in the development of the proposed routing algorithm and the node trust value is evaluated, sensor node misbehavior is identified, and energy conservation is maximized. …”
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