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1
Ant colony optimization in dynamic environments
Published 2010“…In order to achieve this objective, six ant algorithms namely Ant System (AS), Ant Colony System (ACS), Best-Worst Ant System (BWAS), Elitist Ant System (EAS), Max-Min Ant System (MMAS) and Rank-Based Ant System (RBAS) were implemented to solve a dynamic optimization problem in the form of the dynamic Traveling Salesman Problem (TSP). …”
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2
Heterogenous adaptive ant colony optimization with 3-opt local search for the travelling salesman problem
Published 2020“…However, it is well-known that parameters are problem-dependent as different problems or even different instances have different optimal parameter settings. …”
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3
Optimization of turning parameters using ant colony optimization
Published 2008“…This project proposed a new optimization technique based on the ant colony algorithm for solving single-pass turning optimization problems. …”
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4
Reactive approach for automating exploration and exploitation in ant colony optimization
Published 2016“…Ant colony optimization (ACO) algorithms can be used to solve nondeterministic polynomial hard problems. …”
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5
Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter
Published 2017“…This paper presents a hybrid classification algorithm, ACOMV-SVM which is based on ant colony and support vector machine.A new direction for ant colony optimisation is to optimise mixed (discrete and continuous) variables.The optimised variables are then feed into selecting feature subset and tuning its parameters are two main problems of SVM.Most approaches related to tuning support vector machine parameters will discretise the continuous value of the parameters which will give a negative effect on the performance. …”
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6
Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Ant Colony Optimization originally deals with discrete optimization problems. …”
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7
Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm
Published 2023“…This research aims to find the optimal parameter values for the Pareto Ant Colony System (PACS) algorithm, which is used to obtain solutions for the generator maintenance scheduling problem. …”
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8
Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Support Vector Machines are considered to be excellent patterns classification techniques.The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and may be done experimentally through time consuming human experience.To overcome this difficulty, an approach such as Ant Colony Optimization can tune Support Vector Machine parameters.Ant Colony Optimization originally deals with discrete optimization problems. …”
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9
Solving Support Vector Machine Model Selection Problem Using Continuous Ant Colony Optimization
Published 2013“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem.In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a need to discretize the continuously value into discrete value.This discretize process would result in loss of some information and hence affect the classification accuracy and seeking time.This study proposes an algorithm that can optimize Support Vector Machine parameters using Continuous Ant Colony Optimization without the need to discretize continuous value for Support Vector Machine parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed hybrid algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.…”
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10
An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town
Published 2005“…The objectives of this study are to explore and evaluate the Ant System (AS) algorithm and Ant Colony System (ACS) algorithm in finding shortest paths. …”
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11
Optimization of milling parameters using ant colony optimization
Published 2008“…An example to apply the Ant Colony Algorithm to the problem has been presented at the end of the paper to give clear picture from the application of the system and its efficiency. …”
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12
Hybrid ant colony optimization algorithm for container loading problem
Published 2012“…In this study, a Tower Building (TB) heuristic with less complexity, inspired by the stack building heuristic, is proposed to hybridize with an Ant Colony Optimization (ACO) for solving the Container Loading Problem (CLP). …”
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13
Ant system with heuristics for capacitated vehicle routing problem
Published 2013“…As a route improvement strategy, two heuristics which are the swap among routes procedure and 3-opt algorithm are also employed within the ASH algorithm. …”
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14
Incremental continuous ant colony optimization technique for support vector machine model selection problem
Published 2012“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem. …”
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15
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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Nature-inspired parameter controllers for ACO-based reactive search
Published 2015“…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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17
Modified ant colony optimization algorithms for deterministic and stochastic inventory routing problems / Lily Wong
Published 2018“…In order to improve the proposed algorithms, population based ACO where the ants are subdivided into subpopulations and each subpopulation represents one inventory level is proposed. …”
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18
Parameter adaptation for ant colony system in wireless sensor network
Published 2019“…The Ant Colony System (ACS) algorithm has been applied in solving packet routing problems in Wireless Sensor Networks (WSNs). …”
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Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling
Published 2022“…Present graph models cannot generate schedule for the multi-objective GMS models while existing Pareto Ant Colony System (PACS) algorithms were not able to consider the two problems separately. …”
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20
Strategic oscillation for exploitation and exploration of ACS algorithm for job scheduling in static grid computing
Published 2015“…Exploitation and exploration mechanisms are the main components in metaheuristics algorithms. These mechanisms are implemented explicitly in ant colony system algorithm.The rate between the exploitation and exploration mechanisms is controlled using a parameter set by the users of the algorithm. …”
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