Abstract

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.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.