Engineering Design Applications of Dichotomous Search in Shuffled Frog-Leaping Algorithm

Shuffled frog-leaping algorithm (SFLA) is a recent addition to the family of stochastic search methods that mimics the social and natural behavior of species. SFLA combines the advantages of local search process of particle swarm optimization (PSO) and mixing of information of the shuffled complex evolution. The basic idea behind modeling of such algorithms is to achieve near to global solutions to the large scale optimization problems and complex problems which can’t be solved using deterministic or traditional numerical techniques. In Dichotomous Shuffled Frog Leaping Algorithm (D-SFLA) the worst frog position is modified by embedding the concept of bidirectional search. The idea is to search dichotomously in both directions to generate a new trial vector or worst frog position. This paper also includes brief literature review of SFLA and extends the D-SFLA by implementing it to solve engineering design problems. The simulated results are compared with the state-of-art algorithms and illustrate the efficacy of the proposal. Keywords:Shuffled frog leaping algorithm; SFLA;Optimization; Stochastic; Bi-directional search; Engineering Design Problems

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