The Application of Adaptive Genetic Algorithm Based on Output Degree Coding in Production Scheduling Problem

Abstract

Production scheduling problem is an important problem in the production process of enterprises. Its performance directly affects the production efficiency and economic benefits of enterprisesw. When dealing with complex production involving parts processing and workpiece assembly, the existing genetic algorithm, neural network algorithm, ant colony algorithm, migratory bird algorithm and other algorithms have some shortcomings, such as slow convergence, high cost, inaccurate results and so on. In view of these shortcomings, an adaptive genetic algorithm based on in out degree coding is proposed, which improves the coding mode of traditional genetic algorithm and introduces adaptive genetic algorithm. Compared with the quasi- critical path algorithm, the layer priority algorithm and the dynamic critical path algorithm, the experimental results show that the proposed algorithm is stable in the vicinity of the optimal solution in the 14th generation on average, which proves that the improved method can be used to solve the comprehensive job scheduling problem effectively and convergent quickly.