Design and application of scheduling algorithm based on multi-objective and multi- constraint

Aiming at the multi-objective production scheduling problem faced by machining enterprises under multi-constraint conditions such as dual-station, adjacent equipment and out-of-command process, the production factors required for scheduling are analyzed, and the mathematical model of optimal production scheduling is established. An improved genetic algorithm based on dynamic crossover and mutation operator is proposed. Molecular and fission molecules are introduced into the traditional scheduling algorithm based on three-stage coding. Chromosome offset is used to improve the compactness of scheduling and accelerate the convergence speed of algorithm. The scheduling results optimized by weighting coefficient are obtained. Finally, an example is solved and applied to actual production, which greatly improves the efficiency of production scheduling.