![fuzzytime windows fuzzytime windows](https://colbertondemand.com/wp-content/uploads/2019/11/101117-F-4338B-049-1.jpg)
IEEE Transaction on Evolutionary Computation 6: 182-197. A fast and elitist multiobjective genetic algorithm: NSGA-II. Computers and Operations Research 39: 2033-2050. A parallel iterated tabu search heuristic for vehicle routing problems. Cordeau, J.F., Maischberger, M., 2012.Dynamic column generation for dynamic vehicle routing with time windows. Computers and Operations Research 38: 954-966. An ant colony algorithm hybridized with insertion heuristics for the time dependent vehicle routing problem with time windows. Computers and Operations Research 38(6): 954-966. Blaseiro, S.R., Loiseau, I., and Ramonet, J., 2011.Scenariobased planning for partially dynamic vehicle routing with stochastic customers. Bent, R., W., and Van Hentenryck, P., 2004.Expert Systems with Applications 40: 376-383.
![fuzzytime windows fuzzytime windows](https://i.stack.imgur.com/HBo2I.jpg)
A Simulated Annealing-based parallel multiobjective approach to vehicle routing problems with time windows. The computational experiments on data sets represent the efficiency and effectiveness of the proposed approach. To solve this multi-objective model, an evolutionary algorithm is developed to obtain the Pareto solutions and its performance is analyzed on various test problems in the literature. The proposed model is considered as a multi-objective problem where the overall travelling distance, fleet size and waiting time imposed on vehicles are minimized and the customers’ satisfaction or the service level of the supplier to customers is maximized. Moreover, the model tries to characterize the customers’ satisfaction and the service level issues by applying the concept of fuzzy time windows. In this model, all data and information required to the routing process are not known before planning and they revealed dynamically during the routing process and the execution of the routes. This paper studies the multi-objective dynamic vehicle routing and scheduling problem by using an evolutionary method. Seyed Farid Ghannadpour, Mohsen Hooshfar 2015 Abstract SCITEPRESS - SCIENCE AND TECHNOLOGY PUBLICATIONS Multi-objective Evolutionary Method for Dynamic Vehicle Routing and Scheduling Problem with Customers' Satisfaction Level