A genetic algorithm for fuzzy order acceptance and scheduling problem

In light of the imprecise and fuzzy nature of real production environments, the order acceptance and scheduling (OAS) problem is associated with fuzzy processing times, fuzzy sequence dependent set up time and fuzzy due dates. In this study, a genetic algorithm (GA) which uses fuzzy ranking methods is proposed to solve the fuzzy OAS problem. The proposed algorithm is illustrated and analyzed using examples with different order sizes. As illustrative numerical examples, fuzzy OAS problems with 10, 15, 20, 25, 30 and 100 orders are considered. The feasibility and effectiveness of the proposed method are demonstrated. Due to the NP-hard nature of the problem, the developed GA has great importance to obtain a solution even for big scale fuzzy OAS problem.  Also, the proposed GA can be utilized easily by all practitioners via the developed user interface.