Dung beetle inspired local search in artificial bee colony algorithm for unconstrained and constrained numerical optimisation. (16th December 2020)

• Record Type: Journal Article
• Authors: Sharma, Nirmala; Sharma, Harish; Sharma, Ajay; Bansal, Jagdish Chand
• Is Part Of: International journal of intelligent engineering informatics. Volume 8:Number 4(2020)
• Page Start: 268
• Page End: 304
• Publication Date: 2020-12-16
• Subjects: local search -- swarm intelligence -- dung beetle -- nature inspired -- algorithms -- ABC -- artificial bee colony -- natural computing -- artificial intelligence -- optimisation; Artificial intelligence -- Engineering applications -- Periodicals; Engineering -- Computer programs -- Periodicals; Knowledge management -- Periodicals; 620.0028563
• Languages: English
• ISSNs: 1758-8715

Abstract

In recent times, swarm intelligence (SI) centred strategies are proving their efficacy in the arena of engineering optimisation problems. Artificial bee colony (ABC) algorithm is one of the efficient SI centred technique. To intensify exploitation concept of ABC, a local search strategy inspired by dung beetle orientation and foraging activities is developed and amalgamated with ABC. This developed local search strategy is termed as dung beetle local search (DBLS) strategy. The developed amended algorithm is titled as dung beetle inspired ABC (DBABC) algorithm. The developed DBABC is analysed using 32 unconstrained benchmark optimisation problems, 18 constrained benchmark optimisation problems, and 3 engineering design problems. The obtained outcomes validate the competitiveness of the proposed approach.