Hybrid shuffled frog leaping optimisation algorithm for multi-objective optimal design of laminate composites

• New multi-objective optimisation algorithm for solving combinatorial problems.
• Features built-in to maintain perfect balance between intensification and diversification.
• Numerical experiments with varied number of objectives.
• Constraint handling through correction scheme and treating as objective function.
• Comparative performance studies with four popular meta-heuristic algorithms.

In this paper, a hybrid shuffled frog-leaping algorithm (SFLA) is presented for solving multi-objective optimal design of laminate composite structures. A customized neighborhood search algorithm, an adaptive search factor and a crossover operator are suitably incorporated in the proposed algorithm to improve the convergence characteristics apart from features like Pareto dominance, density estimation, and an external archive to store the non-dominated solutions to handle multiple objectives. The performance of the proposed algorithm is demonstrated by solving laminate composite plate, shell and stiffened shell (isogrid) problems. Further, superiority of the proposed algorithm is demonstrated by comparing with four popular meta-heuristic algorithms.