Integrated production and distribution scheduling optimization considering soft time windows and fuzzy travel times
A bi-objective mixed integer nonlinear programming model with total cost of production-inventory-distribution and total weighted early and tardy penalty time is developed for the integrated production and distribution scheduling problem considering soft time windows and fuzzy travel times.A fuzzy weighted superposition operation is de-fined for the calculation of fuzzy weighted penalty times.A three-stage decoding rule is designed based on the structure of the optimization problem,which involves the division of the tour,obtaining the batch manufacturing sequence by calculat-ing the optimal departure time of the tour,and the coordination of batches and tours by a backward adjustment strategy.An improved non-dominated sorting genetic algorithm Ⅱ based on adaptive variable neighborhood search(NSGA-Ⅱ-AVNS)is proposed to solve this problem.Five neighborhood structures with different search properties are designed according to the problem features,and adaptive selection of neighborhood structures to increase the number of executions of excellent neighborhood structures.The neighborhood structure score reset operation is proposed to avoid neighborhood structure se-lection solidification.The experimental results show that the fusion of NSGA-Ⅱ and AVNS has well-balanced exploration and exploitation capabilities of the algorithm,and it is a very competitive method to solve this problem.
integrated production and distribution schedulingsoft time windowsfuzzy travel timesfuzzy weighted superpositionadaptive variable neighborhood searchmultiobjective optimization
万方数据
维普
