Pregled bibliografske jedinice broj: 906972
Ant Colony Algorithms for the Travelling Salesman Problem and the Quadratic Assignment Problem
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 : Delhi: Institution of Engineering and Technology (IET), 2018. str. 409-442
CROSBI ID: 906972 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
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
Institution of Engineering and Technology (IET)
Grad
London : Delhi
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:
Nikola Ivković
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Book Citation Index - Science (BKCI-S)