A Novel Metaheuristic Algorithm Inspired by Rhino Herd Behavior

Gai-Ge Wang, Xiaozhi Gao, Kai Zenger, Leandro dos S. Coelho

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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In this paper paper, inspired by the herding behavior of rhinos, a new kind of swarm-based metaheuristic search method, namely Rhino Herd (RH), is proposed for solving global continuous optimization problems. In various studies of rhinos in nature, the synoptic model is used to describe rhino's space use and estimate its probability of occurrence within a given domain. The number of rhinos increases year by year, and this increment can be forecasted by several population size updating models. Synoptic model and a population size updating model are formalized and generalized to a general-purpose metaheuristic optimization algorithm. In RH, null model without introducing any influences is generated as the initial herding. This is followed by rhino modification via synoptic model. After that, the population size is updated by a certain population size updating model, and newly-generated rhinos are randomly initialized within the given conditions. RH is benchmarked by fifteen test problems in comparison with biogeography-based optimization (BBO) and stud genetic algorithm (SGA). The results clearly show the superiority of RH in searching for the better functi ark problems over BBO and SGA.
Original languageEnglish
Title of host publicationProceedings of The 9th EUROSIM Congress on Modelling and Simulation (EUROSIM 2016), The 57th SIMS Conference on Simulation and Modelling (SIMS 2016)
EditorsEsko Juuso, Erik Dahlquist, Kauko Leiviskä
Number of pages8
ISBN (Electronic)978-91-7685-399-3
Publication statusPublished - 2018
MoE publication typeA4 Article in a conference publication
EventEUROSIM Congress on Modelling and Simulation & SIMS Conference on Simulation and Modelling - Oulu, Finland
Duration: 12 Sep 201616 Sep 2016

Publication series

NameLinköping electronic conference proceedings
PublisherLinköping University Electronic Press
ISSN (Print)1650-3686
ISSN (Electronic)1650-3740


ConferenceEUROSIM Congress on Modelling and Simulation & SIMS Conference on Simulation and Modelling
Abbreviated titleEUROSIM 2016 and SIMS 2016


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