Hybrid Metaheuristics for Multi-Objective Optimization. Issue 1 (March 2015)
- Record Type:
- Journal Article
- Title:
- Hybrid Metaheuristics for Multi-Objective Optimization. Issue 1 (March 2015)
- Main Title:
- Hybrid Metaheuristics for Multi-Objective Optimization
- Authors:
- Talbi, E-G.
- Abstract:
- Over the last two decades, interest on hybrid metaheuristics has risen considerably in the field of multi-objective optimization (MOP). The best results found for many real-life or academic multi-objective optimization problems are obtained by hybrid algorithms. Combinations of algorithms such as metaheuristics, mathematical programming and machine learning techniques have provided very powerful search algorithms. Three different types of combinations are considered in this paper to solve multi-objective optimization problems: Combining metaheuristics with (complementary) metaheuristics. Combining metaheuristics with exact methods from mathematical programming approaches. Combining metaheuristics with machine learning and data mining techniques.
- Is Part Of:
- Journal of algorithms & computational technology. Volume 9:Issue 1(2015)
- Journal:
- Journal of algorithms & computational technology
- Issue:
- Volume 9:Issue 1(2015)
- Issue Display:
- Volume 9, Issue 1 (2015)
- Year:
- 2015
- Volume:
- 9
- Issue:
- 1
- Issue Sort Value:
- 2015-0009-0001-0000
- Page Start:
- 41
- Page End:
- 63
- Publication Date:
- 2015-03
- Subjects:
- Computer algorithms -- Periodicals
Numerical calculations -- Periodicals
Computer algorithms
Numerical calculations
Periodicals
518.1 - Journal URLs:
- http://act.sagepub.com/ ↗
http://www.ingentaconnect.com/content/mscp/jact ↗
http://www.multi-science.co.uk/ ↗ - DOI:
- 10.1260/1748-3018.9.1.41 ↗
- Languages:
- English
- ISSNs:
- 1748-3018
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 6543.xml