Cooperative Co-Evolution and MapReduce: A Review and New Insights for Large-Scale Optimisation

A. N. M. Bazlur Rashid and Tonmoy Choudhury
Additional contact information
A. N. M. Bazlur Rashid: Edith Cowan University, Australia
Tonmoy Choudhury: Edith Cowan University, Australia

International Journal of Information Technology Project Management (IJITPM), 2021, vol. 12, issue 1, 29-62

Abstract: Real-word large-scale optimisation problems often result in local optima due to their large search space and complex objective function. Hence, traditional evolutionary algorithms (EAs) are not suitable for these problems. Distributed EA, such as a cooperative co-evolutionary algorithm (CCEA), can solve these problems efficiently. It can decompose a large-scale problem into smaller sub-problems and evolve them independently. Further, the CCEA population diversity avoids local optima. Besides, MapReduce, an open-source platform, provides a ready-to-use distributed, scalable, and fault-tolerant infrastructure to parallelise the developed algorithm using the map and reduce features. The CCEA can be distributed and executed in parallel using the MapReduce model to solve large-scale optimisations in less computing time. The effectiveness of CCEA, together with the MapReduce, has been proven in the literature for large-scale optimisations. This article presents the cooperative co-evolution, MapReduce model, and associated techniques suitable for large-scale optimisation problems.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJITPM.2021010102 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jitpm0:v:12:y:2021:i:1:p:29-62

Access Statistics for this article

International Journal of Information Technology Project Management (IJITPM) is currently edited by John Wang

More articles in International Journal of Information Technology Project Management (IJITPM) from IGI Global
Bibliographic data for series maintained by Journal Editor ().