Search Results - (( java simulation optimization algorithm ) OR ( colony optimization approach algorithm ))
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Interacted multiple ant colonies optimization approach to enhance the performance of ant colony optimization algorithms
Published 2010“…This paper proposes a new generic algorithmic approach that utilized multiple ant colonies with several new interaction techniques. …”
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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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Optimizing large scale combinatorial problems using multiple ant colonies algorithm based on pheromone evaluation technique
Published 2008“…The approach of using multiple ant colonies is an extension of the Ant Colony Optimization framework. …”
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Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…The two well-known honeybees-based upgraded algorithms, Gbest Guided Artificial Bee Colony (GGABC) and Global Artificial Bee Colony Search (GABCS), use the foraging behavior of the global best and guided best honeybees for solving complex optimization tasks. …”
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Heterogenous adaptive ant colony optimization with 3-opt local search for the travelling salesman problem
Published 2020“…Therefore, this study introduces an adaptive approach to a heterogeneous ant colony population that evolves the alpha and beta controlling parameters for ant colony optimization (ACO) to locate near-optimal solutions. …”
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Ant Colony Optimization With Look Forward Ant In Solving Assembly Line Balancing Problem
Published 2011“…This work presents an approach based on the ant colony optimization technique to address the assembly line balancing problem. …”
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Published 2014“…They are: Global Guided Artificial Bee Colony (GGABC), Improved Gbest Guided Artificial Bee Colony (IGGABC) and Artificial Smart Bee Colony (ASBC) algorithm. …”
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Hybrid ant colony optimization algorithm for container loading problem
Published 2012“…This approach is called, the Hybrid Ant Colony Optimization with Tower Building Heuristic (HACO). …”
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Surface roughness optimization based on hybrid harmony search and artificial bee colony algorithm in electric discharge machining process
Published 2023“…Electric discharges; Optimal systems; Optimization; Surface roughness; Artificial bee colonies (ABC); Artificial bee colony algorithms; Convergence rates; Electric discharge machining (EDM); Hybrid approach; Numerical applications; Optimal solutions; Surface roughness (Ra); Electric discharge machining…”
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Interacted Multiple Ant Colonies for Search Stagnation Problem
Published 2010“…The experimental results show the superiority of the proposed approach than existing one colony ant algorithms like the ant colony system and max-min ant system. …”
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Resource management in grid computing using enhanced ant colony optimization
Published 2010“…Simulation approach has been used to test the performance of the algorithm. …”
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Congestion management based optimization technique using bee colony
Published 2023“…The study involved the development of bee colony algorithm in addressing congestion management, considering cost optimization as the objective function. …”
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Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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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
Published 2010“…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
Published 2012“…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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A noble approach of ACO algorithm for WSN
Published 2018“…In energy compelled wireless sensor networks (WSNs), the means by which to perform effectual routing is among the main focuses. A noble approach of ant colony optimization (ACO) algorithm for discovering the optimum route in the WSNs for data transmission is proposed here for enhancement and optimization considering the issue of path selection to reach the nodes. …”
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Proceeding Paper -
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Enhancement of ant colony optimization in multi-robot source seeking coordination
Published 2019“…In hardware platform, the speed of rotation of the wheel is controlled for various movement such as direct motion and rotation in place. Optimization method is focused on ant colony optimization. …”
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Stagnation control using interacted multiple ant colonies
Published 2009“…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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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier
Published 2013“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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