2013
DOI: 10.3906/elk-1109-44
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An efficient solving of the traveling salesman problem: the ant colony system having parameters optimized by the Taguchi method

Abstract: Abstract:Owing to its complexity, the traveling salesman problem (TSP) is one of the most intensively studied problems in computational mathematics. The TSP is defined as the provision of minimization of total distance, cost, and duration by visiting the n number of points only once in order to arrive at the starting point. Various heuristic algorithms used in many fields have been developed to solve this problem. In this study, a solution was proposed for the TSP using the ant colony system and parameter opti… Show more

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Cited by 45 publications
(15 citation statements)
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References 89 publications
(76 reference statements)
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“…The measure used in Taguchi Method is signal-to-noise (S/N) ratio to measure and esteem the superiority features that is the ratio of signal (S) to the operator of noise (N). Various S/N ratios were presented but three of them are considered standard [48]. The first standard is "smaller-is-better", when the objective account of the quality variable y is zero.…”
Section: Taguchi Methodmentioning
confidence: 99%
“…The measure used in Taguchi Method is signal-to-noise (S/N) ratio to measure and esteem the superiority features that is the ratio of signal (S) to the operator of noise (N). Various S/N ratios were presented but three of them are considered standard [48]. The first standard is "smaller-is-better", when the objective account of the quality variable y is zero.…”
Section: Taguchi Methodmentioning
confidence: 99%
“…It can reduce scrap rates, rework costs, and manufacturing costs due to excessive variability in processes. The Taguchi experimental design aims to minimize the variability in a product or operation in line with a specific function by selecting the most suitable combinations of the controllable factor levels compared to the uncontrollable factors that create variability for a specific product or operation [8]; in this sense, Taguchi parameter design or robust design methodology involves the maximization of performance and quality at minimum cost [9]. This is fundamentally achieved by determining the best settings of those design or process parameters that influence the product performance variation and by fine-tuning those design or process parameters that influence the average performance.…”
Section: Methodsmentioning
confidence: 99%
“…For all the analyzed TSP data sets, the optimum values or the values that are closest to the optimum tour lengths are obtained with the selection of beta as 5. Other best values are obtained when the beta value is selected as 4, random [3][4][5], and 3, respectively. Figures 7 and 8 are plotted to see the convergence rates of ELAMO with respect to the number of iterations and to observe the best routes found for the eil76 and kroA100 data sets.…”
Section: Tsp Instancesmentioning
confidence: 99%
“…These algorithms include simulated annealing, greedy search and genetic algorithms [2][3][4], ant colony optimization and swarm intelligence [5][6][7], discrete cuckoo search [8], and artificial bee colony optimization [9]. However, as accepted in the "no free lunch theorem", there is no metaheuristic algorithm that gives the best performance for all kinds of optimization problems [10].…”
Section: Introductionmentioning
confidence: 99%