Search Results - (( using ant utilizing algorithm ) OR ( evolution optimization path algorithm ))

The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

“…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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Development of an improved GWO algorithm for solving optimal paths in complex vertical farms with multi-robot multi-tasking by Shen, Jiazheng, Hong, Tang Sai, Fan, Luxin, Zhao, Ruixin, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan

“…The EPDE-GWO algorithm is compared with Genetic Algorithm (GA), Simulated Annealing (SA), Dung Beetle Optimizer (DBO), and Particle Swarm Optimization (PSO). …”
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Path optimization using genetic algorithm evolution by Low C.Y., Chong K.H., Salleh K., Johnny K.S.P.

A new multiple ant colonies optimization algorithm utilizing average pheromone evaluation mechanism by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md Norwawi, Norita

“…Multiple ant colonies optimization is an extension of the Ant Colony Optimization framework It offers a good opportunity to improve the ant colony optimization algorithms by encouraging the exploration of a wide area of the search space without losing the chance of exploiting the history of the search.This paper proposes a new multiple ant colonies optimization algorithm that is based on ant colony system and utilizes ave rage pheromone evaluation mechanism.The new algorithm divides the ants’ populations into multiple ant colonies and can be used to tackle large volume combinatorial optimization problems effectively. …”
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Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim by Hashim, Siti Zuraifah

“…Roadways and telephone systems are the examples of them. Genetic Algorithms (GA), pioneered by John Holland, applies the principle of evolution found in nature to the problem of finding an optimal solution. …”
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Differential evolution optimization for constrained routing in Wireless Mesh Networks by Sanni, Mistura Laide, Hassan Abdalla Hashim, Aisha, Hassan, Wan Haslina, Ahmed, Gharib Subhi Mahmoud, Anwar, Farhat, Zakaria, Omar

“…This solution addresses efficient and optimal routing path construction for cost and quality metrics of the application. …”
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Optimizing large scale combinatorial problems using multiple ant colonies algorithm based on pheromone evaluation technique by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md Norwawi, Norita

“…The new algorithm is based on the ant colony system and utilizes average and maximum pheromone evaluation mechanisms. …”
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Hybrid ant colony optimization algorithm for container loading problem by Yap, Ching Nei

“…It was showed that the proposed HACO algorithm has the capability in solving the CLP.…”
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Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization. …”
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An exploration technique for the interacted multiple ant colonies optimization framework by Aljanaby A., Ku-Mahamud K.R., Norwawi N.Md.

Stagnation control using interacted multiple ant colonies by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md Norwawi, Norita

“…Stagnation is a common problem that all ant algorithms suffer from regardless of their application domain.This paper proposes a new algorithmic approach that can effectively be used to tackle combinatorial optimization problems with a good chance to control the stagnation. …”
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New heuristic function in ant colony system for the travelling salesman problem by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

“…Ant Colony System (ACS) is one of the best algorithms to solve NP-hard problems.However, ACS suffers from pheromone stagnation problem when all ants converge quickly on one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic values to calculate the probability of choosing the next node. …”
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Big data clustering using grid computing and ant-based algorithm by Ku-Mahamud, Ku Ruhana

“…This paper presents a framework for big data clustering which utilizes grid technology and ant-based algorithm.…”
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Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

“…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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Power line faults classification by neural network train by Ant Colony Optimization by Nasirudin, Mohd Syafiq

“…The characteristic of ACO algorithms is their explicit use of elements of previous solutions. …”
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New heuristic function in ant colony system for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana, Alobaedy, Mustafa Muwafak

“…Job scheduling problem classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Ant colony system algorithm is a meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This paper focuses on enhancing the heuristic function where information about recent ants’ discoveries will be taken into account.Experiments were conducted using a simulator with dynamic environment features to mimic the grid environment.Results show that the proposed enhanced algorithm produce better output in term of utilization and make span.…”
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Enhanced ant colony optimization for grid load balancing by Mohamed Din, Aniza, Ku-Mahamud, Ku Ruhana, Abdul Nasir, Husna Jamal

“…A simulation environment was developed to test the performance of the algorithm against another ant based algorithm in terms of resource utilization and to determine how different values of evaporation rate resource utilization. …”
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Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application by Hardhienata, Medria Kusuma Dewi, Priandana, Karlisa, Putra, Daffa Rangga, Sriatun, Mamiek, Wulandari, Buono, Agus, Mohamed, Raihani

“…The optimum number of ants and agents in the proposed algorithm was also analysed for robust performance. …”
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An Exploration Technique for the Interacted Multiple Ant Colonies Optimization Framework by Aljanaby, A, Ku-Mahamud, KR, Norwawi, NM

“…These tests also show the capability of IMACO to outperform other well known ant algorithms like ant colony system and max-min ant system.…”

Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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