Branch population genetic algorithm for extension dual resource constrained job shop scheduling problem

In this paper, a hybrid genetic algorithm was proposed for solving extension dual resource constrained job shop scheduling problem. The algorithm was constructed based on inheriting evolution experience of parent population with the branch population. In addition, this algorithm used some optimization operators to optimize algorithm performance, such as the elite evolutionary operator, the roulette selection operator based on sector partition, the variable neighbourhood search operator, and so on. Finally, the optimization performances of above mechanisms were validated according to the statistical analysis on the simulation results of strategies comparison simulation and algorithm performance comparison simulation.