English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper presents an improved version of the animal migration optimization (AMO) algorithm for solving the traveling salesman problem (TSP), which is classified as a combinatorial NP-hard problem. AMO is one of the recent metaheuristic algorithms inspired by the migration behavior of animals and has been efficiently applied to a variety of optimization problems. The algorithm is improved by reconstructing the neighborhood topology of each animal during the migration. This modified algorithm is called the elitist animal migration optimization (ELAMO) algorithm, since elitism is introduced as a way in which the positions of the leaders are considered for the neighborhood scheme. To observe the performance of ELAMO, it is compared with AMO and some efficient algorithms. The experimental results showed that the ELAMO algorithm has improved the solution quality of AMO and has produced effective or even competitive values for the selected TSP data sets.

An elitist approach for solving the traveling salesman problem using an animal migration optimization algorithm