Memetic Algorithm with Exchange Coding for Intelligent Scheduling Optimization

In response to the limited and fixed scheduling patterns in existing intelligent scheduling technologies, this paper proposes a Memetic algorithm with Exchange Coding (MA-EC) based on flexible and non-uniform work schedules to develop rational scheduling plans that meet the needs of employees and production plans, thereby improving employee satisfaction and enhancing enterprise competitiveness. Firstly, three-dimensional binary coding is used to clearly express population individuals. Secondly, a greedy initialization of population individuals is performed to meet work requirements. Thirdly, the exchange coding method is utilized to update the population and reduce the search space, accelerating the convergence rate of the algorithm. Finally, a local search based on employee preferences is designed to avoid the algorithm from getting trapped in local optima and enhance the global search ability of the algorithm. Experimental results on instances with nine problem scales generated randomly show that compared with competing algorithms, the proposed algorithm has faster convergence speed, higher search efficiency, and can obtain intelligent scheduling plans with higher employee satisfaction.