A model for priority processing of orders based on Genetic Algorithm and Membership Function

Order arrangement is always the headache thing for manufacturers even in this high-tech modern society. Hence, this paper manages to construct a nonlinear 0-1 programming mathematical model in search of optimal solution of minimizing the cost of default. And we make an attempt to apply Genetic Algorithm in accordance with this NP-hard problem. In designing the algorithm, we propose an encoding method based both on orders and working procedure, adopt Roulette Wheel method to select the next generation, and embed crossover and mutation to avoid the common defect of premature convergence. Noticing that firms would have various psychological preferences towards different orders, we introduce Membership Function to characterize the priority of orders by comprehensively concern processing complexity, urgency and revenue of orders.