Novel Multiobjective Shuffled Frog Leaping Algorithm with Application to Reservoir Flood Control Operation

Reservoir flood control operation (RFCO) is a large scale multiobjective problem with complex constraints that require powerful algorithms to solve it. As a new metaheuristic evolutionary algorithm, shuffled frog leaping algorithm (SFLA) has the potential ability to solve multiobjective optimization problems because of its group evolution characteristic. In this paper, we present a novel multiobjective shuffled frog leaping algorithm (MOSFLA), which incorporates an archiving strategy based on self-adaptive niche method to maintain the nondominated solutions, and improves the memetic evolution process of SFLA to adapt to the multiobjective optimization problem. The numerical experiments of five Zitzler-Deb-Thiele functions indicate that MOSFLA yields better-spread solutions and converges closer to the true Pareto frontier than non-denominated sorting genetic algorithm (NGSA)-II and SPEA2. Furthermore, MOSFLA is applied to solve RFCO of the Three Gorges Project, and the results demonstrate that this algorit...