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Ant Colony Algorithms for the Travelling Salesman Problem and the Quadratic Assignment Problem


Ivković, Nikola
Ant Colony Algorithms for the Travelling Salesman Problem and the Quadratic Assignment Problem // Swarm Intelligence. Volume 1 : Principles, Current Algorithms and Methods / Tan, Ying (ur.).
London, United Kingdom: IET, 2018. str. 409-442


Naslov
Ant Colony Algorithms for the Travelling Salesman Problem and the Quadratic Assignment Problem

Autori
Ivković, Nikola

Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni

Knjiga
Swarm Intelligence. Volume 1 : Principles, Current Algorithms and Methods

Urednik/ci
Tan, Ying

Izdavač
IET

Grad
London, United Kingdom

Godina
2018

Raspon stranica
409-442

ISBN
978-1-78561-627-3

Ključne riječi
ant colony optimization ; Ant System Elitist ; Ant System ; Ant Colony System ; Rank-Based Ant System ; Approximate Nondeterministic Tree Search ; MAX-MIN Ant System ; Best-Worst Ant System ; Population Based Ant Colony Optimization ; Three Bound Ant System ; local optimization ; parameter settings

Sažetak
The ant colony optimization (ACO) is a metaheuristic which has been successfully used to solve computationally difficult optimization problems, especially combinatorial optimization problems which belong to the class of NP-hard problems. This chapter explains ACO algorithms, their most important variants, and hybridization with local optimization methods. Practical considerations for successful ACO implementation and parameter setting are given. The working of the algorithm is explained in details by using simple examples. The chapter ends with overview of research trends in ACO.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo



POVEZANOST RADA


Ustanove
Fakultet organizacije i informatike, Varaždin

Profili:

Avatar Url Nikola Ivković (autor)

Citiraj ovu publikaciju

Ivković, Nikola
Ant Colony Algorithms for the Travelling Salesman Problem and the Quadratic Assignment Problem // Swarm Intelligence. Volume 1 : Principles, Current Algorithms and Methods / Tan, Ying (ur.).
London, United Kingdom: IET, 2018. str. 409-442
Ivković, N. (2018) Ant Colony Algorithms for the Travelling Salesman Problem and the Quadratic Assignment Problem. U: Tan, Y. (ur.) Swarm Intelligence. Volume 1 : Principles, Current Algorithms and Methods. London, United Kingdom, IET, str. 409-442.
@inbook{inbook, author = {Ivkovi\'{c}, N.}, editor = {Tan, Y.}, year = {2018}, pages = {409-442}, keywords = {ant colony optimization, Ant System Elitist, Ant System, Ant Colony System, Rank-Based Ant System, Approximate Nondeterministic Tree Search, MAX-MIN Ant System, Best-Worst Ant System, Population Based Ant Colony Optimization, Three Bound Ant System, local optimization, parameter settings}, isbn = {978-1-78561-627-3}, title = {Ant Colony Algorithms for the Travelling Salesman Problem and the Quadratic Assignment Problem}, keyword = {ant colony optimization, Ant System Elitist, Ant System, Ant Colony System, Rank-Based Ant System, Approximate Nondeterministic Tree Search, MAX-MIN Ant System, Best-Worst Ant System, Population Based Ant Colony Optimization, Three Bound Ant System, local optimization, parameter settings}, publisher = {IET}, publisherplace = {London, United Kingdom} }