Search Results - between ((ant algorithm) OR (path algorithm))

Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff by Sariff, Nohaidda

“…The main goal of this research is to compare the performances between Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithm. …”
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Evaluation of robot path planning algorithms in global static environments: genetic algorithm vs ant colony optimization algorithm / Nohaidda Sariff and Norlida Buniyamin by Sariff, Nohaidda, Buniyamin, Norlida

“…This paper presents the application of Genetic Algorithm and Ant Colony Optimization (ACO) Algorithm for robot path planning (RPP) in global static environment. …”
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Simulation of identifying shortest path walkway in library by using ant colony optimization by Chui Teng, Chan

“…A research is proposed based on Ant Colony Optimization for solving the shortest path problem in library.This is a research that the algorithm is aim to implement on a robot. …”
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Autonomous mobile robots path planning with integrative edge cloud-based ant colony optimization by Nor Azmi, Siti Nur Lyana Karmila, Anwar Apandi, Nur Ilyana, Rafique, Majid, Muhammad, Nor Aishah

“…To address these challenges, this study proposes an Integrative Edge Cloud-Based Ant Colony Optimization (IECACO) algorithm. IECACO incorporates a novel path retrieval mechanism and edge cloud computing infrastructure to minimize redundant path computation and improve convergence efficiency. …”
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AntNet: a robust routing algorithm for data networks by Haseeb, Shariq, Sidek, Khairul Azami, Ismail, Ahmad Faris, Weng Kin, Lai, Yit Mei, Aw

“…It is a combination of both static and dynamic routing algorithms. In this algorithm, a group of mobile agents (compared to real ants) form paths between source and destination nodes. …”
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A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots by Ismail, Amelia Ritahani, Tumian, Afidalina

“…The main idea in this algorithm is the indirect communication between the ants which is established by the means of pheromones in finding the shortest path between their nest and food [14]. …”
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High Rise Building Evacuation Route Model Using DIJKSTRA'S Algorithm by Mohd Sabri, Nor Amalina

“…As a result, the evacuation route model is able to gain the shortest path and safest path consistently between Dijkstra’s algorithms and hybrid version which is Dijkstra-Ant Colony Optimization (DACO). …”
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Optimization of multi-holes drilling path using particle swarm optimization by Najwa Wahida, Zainal Abidin

“…The performance of PSO was then compared with other meta-heuristic algorithms, including Genetic Algorithm (GA) and Ant Colony Optimisation (ACO), Whale Optimisation Algorithm (WOA), Ant Lion Optimiser (ALO), Dragonfly Algorithm (DA), Grasshopper Optimisation Algorithm (GOA), Moth Flame Optimisation (MFO) and Sine Cosine Algorithm (SCA). …”
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Ant system with heuristics for capacitated vehicle routing problem by Tan, Wen Fang

“…The aim of this research is to develop an Ant Colony Optimization (ACO) for solving the CVRP where it simulates the behavior of real ants that always find the shortest path between their nest and a food source through an indirect form of communication, namely pheromone trail. …”
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An efficient algorithm to improve oil-gas pipelines path by Hasan Almaalei, Nabeel Naeem, Mohd Razali, Siti Noor Asyikin, Mohammed Alduais, Nayef Abdulwahab

“…In order to show the efficiency of the proposed algorithm, comparison between ant colony optimization (ACO) algorithm and a real current meth-od of linking is used for this purpose. …”
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A Novel Integrating Between Tool Path Optimization Using An ACO Algorithm And Interpreter For Open Architecture CNC System by Yusof, Yusri, Latif, Kamran, Hatem, Noor, A. Kadir, Aini Zuhra, Mohammed, M.A

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Gait identification and optimisation for amphi-underwater robot by using ant colony algorithm by Mohd Yusof, Muhammad Syafiq, Toha @ Tohara, Siti Fauziah

“…For the optimization, the robot will travel from one specific point to another with the predefined position within optimized gait and fastest time by using Ant Colony Optimization (ACO) technique. The algorithm being compared, between Ant Colony Algorithm (ACO) and the Particle Swarm Optimisation (PSO) in terms of time and distance. …”
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Articulated robots motion planning using foraging ant strategy by Mohamad, Mohd. Murtadha

“…This paper proposes a novel search technique, the F-Ant algorithm, in order to find a reliable path between the initial configuration and the goal configuration of the articulated robot. …”
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Comparison between ant colony and genetic algorithm using traveling salesman problem by Abduljabbar, Zaid Ammen, Khalefa, Mustafa S., A. Jabar, Marzanah

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Optimization And Execution Of Multiple Holes-Drilling Operations Based On STEP-NC by Yusof, Yusri, Latif, Kamran, Hatem, Noor, A. Kadir, Aini Zuhra, Abedlhafd, Mohammed M.

“…The newly developed system combines between open CNC control system and ant colony optimization (ACO) algorithm by using LabVIEW software. …”
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An Enhanced Ant Colony Optimisation Algorithm with the Hellinger Distance for Shariah-Compliant Securities Companies Bankruptcy Prediction by Zainol, Annuur Zakiah, Saian, Rizauddin, Teoh, Yeong Kin, Mohd Razali, Muhammad Hasbullah, Abu Bakar, Sumarni

“…Hence, this study proposes an improved algorithm, the Hellinger Distance Ant-Miner (HD-AntMiner), which employs Hellinger distance as the heuristic for ants to gauge the similarity or dissimilarity between probability distributions. …”
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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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New heuristic function in ant colony system algorithm by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza, Yusof, Yuhanif, Mahmuddin, Massudi, Alobaedy, Mustafa Muwafak

“…NP-hard problem can be solved by Ant Colony System (ACS) algorithm.However, ACS suffers from pheromone stagnation problem, a situation when all ants converge quickly to one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic value to calculate the probability of choosing the next node.However, the heuristic value is not updated throughout the process to reflect new information discovered by the ants.This paper proposes a new heuristic function for the Ant Colony System algorithm that can reflect new information discovered by ants.The credibility of the new function was tested on travelling salesman and grid computing problems.Promising results were obtained when compared to classical ACS algorithm in terms of best tour length for the travelling sales-man problem. …”
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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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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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