Nature-inspired optimization method: Hydrozoan algorithm for solving continuous problems

Tansui, Daranat; Thammano, Arit

doi:10.1109/snpd.2017.8022695

Cited by 4 publications

(1 citation statement)

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“…SQP solved small size problems efficiently; however, WCMFO was the best method for medium and large problems. Tansui and Thammano [38] developed Hydrozoan Algorithm (HA) based on the life cycle of hydrozoans, especially regeneration and transplantation, which included the formation of new animals, that are genetically different from their parents, as well as new ones, that are genetically identical to their parents. HA was specifically designed to find the best solutions for continuous optimization problems.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Nature-Inspired Optimization Algorithm: Hydrozoan and Sea Turtle Foraging Algorithms for Solving Continuous Optimization Problems

Tansui

Thammano

2020

IEEE Access

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In this paper, we develop a hybrid optimization algorithm inspired by the reproduction processes of hydrozoans and the foraging behavior of sea turtles for solving continuous optimization problems. Our hybrid algorithm combines the exploration capability of the hydrozoan algorithm with the exploitation capability of the sea turtle foraging algorithm. Moreover, a new adaptive crossover operator was introduced and integrated into the hybrid algorithm to further enhance exploration capability. Our hybrid algorithm was evaluated and compared to the individual algorithms and 12 state-of-the-art algorithms. Results on 21 standard benchmark functions showed that our algorithm was very effective and was among the best of the group, specifically it converged faster than the individual algorithms on most functions and reached optimal or near-optimal results on all functions. INDEX TERMS Hybrid algorithm, hydrozoan, nature-inspired algorithm, optimization, sea turtle.

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Section: Introductionmentioning

confidence: 99%