Barnacles mating optimizer: a bio-inspired algorithm for solving optimization problems

• Main Authors: Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Mohd Mawardi, Saari, Hamdan, Daniyal, Mohd Razali, Daud, Saifudin, Razali, Amir Izzani, Mohamed
• Format: Book Section
• Language: English; English
• Published: Springer Singapore 2018
• Subjects: QA76 Computer software; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/22091/13/38.%20Barnacles%20mating%20optimizer-%20a%20bio-inspired%20algorithm%20for%20solving%20optimization%20porblems.pdf; http://umpir.ump.edu.my/id/eprint/22091/14/38.1%20Barnacles%20mating%20optimizer-%20a%20bio-inspired%20algorithm%20for%20solving%20optimization%20porblems.pdf; http://umpir.ump.edu.my/id/eprint/22091/; https://link.springer.com/chapter/10.1007/978-981-13-3708-6_18

A novel bio-inspired optimization algorithm is proposed in this paper namely barnacles mating optimization (BMO) algorithm. The main inspiration of BMO is originated from the mating behavior of barnacles in nature. Barnacles are hermaphroditic micro-organisms which have both male and female sex reproductions. To create new off-springs, they must be fertilized by a neighbor. They are well-known for their long penises, about seven times the length of their bodies to cope with the changing tides and sedentary lifestyle. In BMO, the selection of barnacle’s parents is decided randomly by the length of barnacle’s penis to create new off-springs. The exploitation and exploration processes are the generation of new off-springs inspired by the Hardy-Weinberg principle and sperm cast situation, respectively. The effectiveness of proposed BMO is tested through a set of benchmark multi-dimensional functions which the global and local minimum are known. Comparisons with other recent algorithms also will be presented in this paper.