A New Ant Supervised-PSO Variant Applied to Traveling Salesman Problem A New Ant Supervised-PSO Variant Applied to Traveling Salesman Problem A New Ant Supervised-PSO Variant Applied to Traveling Salesman Problem A New Ant Supervised-PSO Variant Applied to Traveling Salesman Problem
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86100124" target="_blank" >RIV/61989100:27240/16:86100124 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1007/978-3-319-27221-4_8" target="_blank" >http://dx.doi.org/10.1007/978-3-319-27221-4_8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-27221-4_8" target="_blank" >10.1007/978-3-319-27221-4_8</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
A New Ant Supervised-PSO Variant Applied to Traveling Salesman Problem A New Ant Supervised-PSO Variant Applied to Traveling Salesman Problem A New Ant Supervised-PSO Variant Applied to Traveling Salesman Problem A New Ant Supervised-PSO Variant Applied to Traveling Salesman Problem
Popis výsledku v původním jazyce
The Traveling Salesman Problem (TSP) is one of the standard test problems often used for benchmarking of discrete optimization algorithms. Several meta-heuristic methods, including ant colony optimization (ACO), particle swarm optimization (PSO), bat algorithm, and others, were applied to the TSP in the past. Hybrid methods are generally composed of several optimization algorithms. Ant Supervised by Particle Swarm Optimization (AS-PSO) is a hybrid schema where ACO plays the role of the main optimization procedure and PSO is used to detect optimum values of ACO parameters α, β, the amount of pheromones T and evaporation rate ρ. The parameters are applied to the ACO algorithm which is used to search for good paths between the cities. In this paper, an Extended AS-PSO variant is proposed. In addition to the previous version, it allows to optimize the parameter, T and the parameter, ρ. The effectiveness of the proposed method is evaluated on a set of well-known TSP problems. The experimental results show that both the average solution and the percentage deviation of the average solution to the best known solution of the proposed method are better than others methods.
Název v anglickém jazyce
A New Ant Supervised-PSO Variant Applied to Traveling Salesman Problem A New Ant Supervised-PSO Variant Applied to Traveling Salesman Problem A New Ant Supervised-PSO Variant Applied to Traveling Salesman Problem A New Ant Supervised-PSO Variant Applied to Traveling Salesman Problem
Popis výsledku anglicky
The Traveling Salesman Problem (TSP) is one of the standard test problems often used for benchmarking of discrete optimization algorithms. Several meta-heuristic methods, including ant colony optimization (ACO), particle swarm optimization (PSO), bat algorithm, and others, were applied to the TSP in the past. Hybrid methods are generally composed of several optimization algorithms. Ant Supervised by Particle Swarm Optimization (AS-PSO) is a hybrid schema where ACO plays the role of the main optimization procedure and PSO is used to detect optimum values of ACO parameters α, β, the amount of pheromones T and evaporation rate ρ. The parameters are applied to the ACO algorithm which is used to search for good paths between the cities. In this paper, an Extended AS-PSO variant is proposed. In addition to the previous version, it allows to optimize the parameter, T and the parameter, ρ. The effectiveness of the proposed method is evaluated on a set of well-known TSP problems. The experimental results show that both the average solution and the percentage deviation of the average solution to the best known solution of the proposed method are better than others methods.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
IN - Informatika
OECD FORD obor
—
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2016
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Advances in Intelligent Systems and Computing. Volume 420
ISBN
978-3-319-27220-7
ISSN
2194-5357
e-ISSN
—
Počet stran výsledku
15
Strana od-do
87-101
Název nakladatele
Springer Verlag
Místo vydání
London
Místo konání akce
Soul
Datum konání akce
16. 11. 2015
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
000369536900008