A hybrid algorithm based on simplex search and differential evolution for hybrid flow-shop scheduling

An effective hybrid algorithm by merging the searching mechanisms of Nelder-Mead (NM) simplex method and differential evolution (DE) is proposed to solve the hybrid flow-shop problem (HFSP) in this paper. By using a special encoding, the NM and DE methods can be used to solve permutation based combinatorial optimization problems. By combining the DE based global search and NM method based local search, the exploration and exploitation abilities are enhanced and well balanced for solving the HFSP. Numerical testing results and comparisons show that the proposed algorithm is effective, efficient and robust in solving the HFSP.