The Hybrid Shuffle Frog Leaping Algorithm Based on Cuckoo Search for Flow Shop Scheduling with the Consideration of Energy Consumption

Abstract

Green manufacturing requires full consideration of energy-related optimization objective. This paper presents a hybrid shuffle frog leaping algorithm based on the cuckoo search algorithm (HFLCS), and the algorithm for solving multi-objective based green flow shop scheduling problem (MOPFS), the optimization objectives are the maximum completion time and energy consumption. Since the traditional flow shop scheduling problem (PFS) is a typical NP-hard combinatorial problem, MOPFS is also a NP-hard combinatorial problem. Firstly, the levy flight update formula in cuckoo algorithm is based on the update formula of global search, and its nature can make the search out of the local optimum and generate the disturbance; secondly, a global search mechanism based on shuffled frog leaping algorithm and levy flight (LACS) is designed to explore the solution space; thirdly, a multi-neighborhood local search is proposed to search potential solutions in better space. With the application of global search and local search, we can prevent the algorithm iteration from getting into local optimum and find high quality solutions so that we can solve the problem of MOPFS. Finally, the simulation results and comparisons demonstrate the superiority of HFLCS in terms of search quality, robustness, and efficiency.