A new algorithm for multilevel optimization problems using evolutionary strategy, inspired by natural adaptation

Surafel Luleseged Tilahun, Semu Mitiku Kassa, Hong Choon Ong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

Multilevel optimization problems deals with mathematical programming problems whose feasible set is implicitly determined by a sequence of nested optimization problems. These kind of problems are common in different applications where there is a hierarchy of decision makers exists. Solving such problems has been a challenge especially when they are non linear and non convex. In this paper we introduce a new algorithm, inspired by natural adaptation, using (1+1)-evolutionary strategy iteratively. Suppose there are k level optimization problem. First, the leader's level will be solved alone for all the variables under all the constraint set. Then that solution will adapt itself according to the objective function in each level going through all the levels down. When a particular level's optimization problem is solved the solution will be adapted the level's variable while the other variables remain being a fixed parameter. This updating process of the solution continues until a stopping criterion is met. Bilevel and trilevel optimization problems are used to show how the algorithm works. From the simulation result on the two problems, it is shown that it is promising to uses the proposed metaheuristic algorithm in solving multilevel optimization problems.

Original languageEnglish
Title of host publicationPRICAI 2012
Subtitle of host publicationTrends in Artificial Intelligence - 12th Pacific Rim International Conference on Artificial Intelligence, Proceedings
Pages577-588
Number of pages12
DOIs
Publication statusPublished - Oct 25 2012
Event12th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2012 - Kuching, Malaysia
Duration: Sep 3 2012Sep 7 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7458 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2012
CountryMalaysia
CityKuching
Period9/3/129/7/12

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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    Tilahun, S. L., Kassa, S. M., & Ong, H. C. (2012). A new algorithm for multilevel optimization problems using evolutionary strategy, inspired by natural adaptation. In PRICAI 2012: Trends in Artificial Intelligence - 12th Pacific Rim International Conference on Artificial Intelligence, Proceedings (pp. 577-588). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7458 LNAI). https://doi.org/10.1007/978-3-642-32695-0_51