Solving Job-Shop Scheduling Problem by an Improved Genetic Algorithm

An improved genetic algorithm is proposed by introducing selection operation and crossover operation, which overcomes the limitations of the traditional genetic algorithm, avoids the local optimum, improves its convergence rate and the diversity of population, and solves the problems of population prematurity and slow convergence rate in the basic genetic algorithm. Simulation results show that compared with other improved genetic algorithms, the proposed algorithm is better in finding global optimal and convergent rate.