Fuzzy algorithm for fuzzy production scheduling

Two novel fuzzy optimization algorithms were proposed to solve one class of fuzzy programming problem with fuzzy coefficients for production scheduling. Unsatisfying function was adopted to replace membership function, and genetic algorithm was developed, in which the initial population was generated through the hierarchical structure and fuzzy information was incorporated. By the proposed approaches, higher efficiency and better solutions comparing with other fuzzy algorithms is obtained. Finally, the validity of the algorithms is demonstrated by a numerical example on one production scheduling problem.