Research of job-shop scheduling problem based on improved crossover strategy genetic algorithm

The article proposes a crossover strategy improved genetic algorithm to solve the shop scheduling problem for the traditional genetic algorithm. The algorithm uses coding method, based on the process and the introduction of the linear weighted fitness function, the greedy count sub-fitness ratio algorithm combined select operation. The improved algorithm is able to improve search efficiency, accuracy, and avoid premature shortcomings.