Migration Algorithm: A New Human-Based Metaheuristic Approach for Solving Optimization Problems

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F23%3A50020392" target="_blank" >RIV/62690094:18470/23:50020392 - isvavai.cz</a>

Result on the web

<a href="https://www.techscience.com/CMES/online/detail/19111" target="_blank" >https://www.techscience.com/CMES/online/detail/19111</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.32604/cmes.2023.028314" target="_blank" >10.32604/cmes.2023.028314</a>

Result language

angličtina

Original language name

Migration Algorithm: A New Human-Based Metaheuristic Approach for Solving Optimization Problems

Original language description

This paper introduces a new metaheuristic algorithm called Migration Algorithm (MA), which is helpful in solving optimization problems. The fundamental inspiration of MA is the process of human migration, which aims to improve job, educational, economic, and living conditions, and so on. The mathematical modeling of the proposed MA is presented in two phases to empower the proposed approach in exploration and exploitation during the search process. In the exploration phase, the algorithm population is updated based on the simulation of choosing the migration destination among the available options. In the exploitation phase, the algorithm population is updated based on the efforts of individuals in the migration destination to adapt to the new environment and improve their conditions. MA&apos;s performance is evaluated on fifty-two standard benchmark functions consisting of unimodal and multimodal types and the CEC 2017 test suite. In addition, MA&apos;s results are compared with the performance of twelve well-known metaheuristic algorithms. The optimization results show the proposed MA approach&apos;s high ability to balance exploration and exploitation to achieve suitable solutions for optimization problems. The analysis and comparison of the simulation results show that MA has provided superior performance against competitor algorithms in most benchmark functions. Also, the implementation of MA on four engineering design problems indicates the effective capability of the proposed approach in handling optimization tasks in real-world applications.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Computer Modeling in Engineering &amp; Sciences

ISSN

1526-1492

e-ISSN

1526-1506

Volume of the periodical

137

Issue of the periodical within the volume

2

Country of publishing house

US - UNITED STATES

Number of pages

36

Pages from-to

1695-1730

UT code for WoS article

000962854800001

EID of the result in the Scopus database

2-s2.0-85165172667