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Ant Colony Algorithms for the Travelling Salesman Problem and the Quadratic Assignment Problem (CROSBI ID 59854)

Prilog u knjizi | izvorni znanstveni rad | međunarodna recenzija

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 : Delhi: Institution of Engineering and Technology (IET), 2018. str. 409-442

Podaci o odgovornosti

Ivković, Nikola

engleski

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

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.

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

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Podaci o prilogu

409-442.

objavljeno

Podaci o knjizi

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

Tan, Ying

London : Delhi: Institution of Engineering and Technology (IET)

2018.

978-1-78561-627-3

Povezanost rada

Računarstvo