Research Repository

Diversity maintenance using a population of repelling random-mutation hill climbers

Fairbank, MH and Volkovas, R and Perez-Liebana, D (2017) Diversity maintenance using a population of repelling random-mutation hill climbers. In: Computer Science and Electronic Engineering (CEEC), 2017-09-27 - 2017-09-29, University of Essex.

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A novel evolutionary algorithm, which can be viewed as an extension to the simple, yet effective, approach of the Random-Mutation Hill Climber (RMHC), is presented. The algorithm addresses the shortcomings of RMHC and its multi-individual parallel version through the introduction of a penalty term into the fitness function, which penalizes individuals in the population for being too similar, hence maintaining population diversity. The performance of the algorithm is evaluated on the deceptive trap and a set of SAT problems, comparing them to the Crowding EA. The results show that at a small cost of solution speed on simpler problems, the algorithm gains better capabilities of dealing with the issues of local maxima.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: _not provided_
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 31 Jan 2018 13:53
Last Modified: 15 Jan 2022 01:22

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