An Improved Genetic Algorithm for Multiple-Machine Scheduling Problem

Genetic algorithm (GA) is one of the most effective methods to solve combination optimal problem of machine scheduling. The aspect application of GA is limited because limitations of itself. The paper purposes an improved GA with self adaptation selection of crossover probability and mutation probability, and non-equiprobability selection of crossover sites through analyzing the limitation of rareripe and heterogeneous search. The application and simulation in a steel rope enterprise multiple-machine scheduling problem are given using the method. The result is correct and rational.