Application of Shuffled Frog Leaping Algorithm to an Uncapacitated SLLS Problem

Shuffled frog leaping algorithm (SFLA) is a population-based novel and effective meta-heuristics computing method, which received increasing focuses from academic and engineering optimization fields in recent years. Since SFLA is a combination of Memetic algorithm (MA) with strong local search (LS) ability and particle swarm optimization (PSO) with good global search (GS) capability, it is of strong optimum-searching power and easy to be implemented. This paper is devoted to investigate the ability of shuffled frog leaping algorithm (SFLA) to solve an uncapacitated single level lot-sizing (SLLS) problem. Through comparing with some heuristic algorithms, the result showed the feasibility and effectiveness of SFLA.