Pruned search: A machine learning based meta-heuristic approach for constrained continuous optimization

Ruoqian Liu, Ankit Agrawal, Wei Keng Liao, Alok Choudhary, Zhengzhang Chen

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

5 Scopus citations

Abstract

Searching for solutions that optimize a continuous function can be difficult due to the infinite search space, and can be further complicated by the high dimensionality in the number of variables and complexity in the structure of constraints. Both deterministic and stochastic methods have been presented in the literature with a purpose of exploiting the search space and avoiding local optima as much as possible. In this research, we develop a machine learning framework aiming to 'prune' the search effort of both types of optimization techniques by developing meta-heuristics, attempting to knowledgeably reordering the search space and reducing the search region. Numerical examples demonstrate that this approach can effectively find the global optimal solutions and significantly reduce the computational time for seven benchmark problems with variable dimensions of 100, 500 and 1000, compared to Genetic Algorithms.

Original languageEnglish (US)
Title of host publication2015 8th International Conference on Contemporary Computing, IC3 2015
EditorsJ. Amudha, Deepa Gupta, Jaric Zola, Narendra Nanjangud, Animesh Pathak, Sushil K. Prasad, Tirumale Ramesh, Manish Parashar, Kishore Kothapalli, Purushotham Bangalore, Sanjay Chaudhary, K. V. Dinesha
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages13-18
Number of pages6
ISBN (Electronic)9781467379489
DOIs
StatePublished - Dec 3 2015
Event8th International Conference on Contemporary Computing, IC3 2015 - Noida, India
Duration: Aug 20 2015Aug 22 2015

Publication series

Name2015 8th International Conference on Contemporary Computing, IC3 2015

Other

Other8th International Conference on Contemporary Computing, IC3 2015
CountryIndia
CityNoida
Period8/20/158/22/15

Keywords

  • Complexity reduction
  • Constrained optimization
  • Machine learning
  • Meta-heuristics

ASJC Scopus subject areas

  • Software

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