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In this paper, a dynamic vehicle routing problem (DVRP) is solved based on hybrid predictive control strategy with an objective function that includes two dimensions: user and operator costs. To handle some undesired assignments for the users, a new objective function is designed, able to carry out the fact that some users can become particularly annoyed if their service is postponed. Genetic algorithms...
This paper presents a genetic algorithm coordinated by fuzzy rule models to solve the vehicle routing problem with time windows. The fuzzy rule-based coordinators play distinct roles during the genetic algorithm execution. The aim is to trade-off exploration and exploitation behavior for route and distance minimization. Experimental results using classic benchmark test instances suggest that the fuzzy...
A preliminary study combining two diversity measures with an accuracy measure in two bicriteria fitness functions to genetically select fuzzy rule-based multiclassification systems is conducted in this paper. The fuzzy rule-based classification system ensembles are generated by means of bagging and mutual information-based feature selection. Several experiments were developed using four popular UCI...
Computational intelligence competitions have recently gained a lot of interest. These contests motivate and encourage researchers to participate on them, and to apply their work areas to specific games. During the last two years, one of the most popular competitions held on computational intelligence in games conferences is the car racing competition. This competition combines the fun of driving to...
In this paper, the vehicle routing problem with fuzzy demands is considered, and in view of vehicle routing problem of multi-vehicle single cart yard has uncertain demand, a multi-objection fuzzy chance constrained program is designed based on fuzzy credibility theory. Then the hybrid genetic algorithm based on fuzzy simulation is given to solve the vehicle routing model. At the same time, the influence...
With the intensification of market competition and fast development of science and technology, many enterprises have begun to realize the importance of logistic distribution vehicle routing problem under uncertainty environment, and begin to pay more attention to the research of this problem. In this paper, The traditional vehicle routing problem with time windows is expanded to the situation that...
In order to reduce the delay of vehicles passing through junction, the signal timing of agent controlled intersection was optimized by Q-Learning approach. On the basis of fuzzy rule set, the effect of signal control was improved through optimizing the combination of control rules with Q-Learning. The result of simulation illustrates that the signal control method based on Q-Learning is better than...
In this paper, the multiple-depot vehicle routing problem with fuzzy demands is considered, on the basis of uncertain demand of multiple-depot vehicle routing problem, a fuzzy chance constrained program is designed based on fuzzy credibility theory. Then the hybrid genetic algorithm based on fuzzy simulation is used to solve the vehicle routing model. In genetic algorithm, a new code is given, and...
The traditional deterministic vehicle routing problem (VRP) is expanded to the situation that the VRP has fuzzy travel time features. After a simple description of the VRP with fuzzy traveling time, a mathematical model for the problem is built. Then, we put forward the concept of level effect function L(lambda), established a very practical and workable measurement method IL - which can quantify...
The Multi-Depot Vehicle Routing Problem with time-dependent and fuzzy travel time is very difficult to solve to optimality even for relatively small size instances. So few or no literatures have focused on the problem so far. But it is very close to real world and can make the schedule more availability and more flexible. So this paper focuses on modeling and solution of the problem. A model of MDVRPTW...
The paper presents a model of the real world vehicle routing and dispatching problem. In real world, vehicle travel speeds are varying with period of time and can not be expressed as exact values. So the time-dependent and fuzzy travel speeds are introduced into the model. A dispatching period is divided into some time slices and each time slice is designated a triangular fuzzy speed. The travel time...
In this contribution we explore the combination of bagging with random subspace and two variants of Battiti's mutual information feature selection methods to design fuzzy rule-based classification system ensembles. Besides, we consider a multicriteria genetic algorithm guided by the training error to select the component classifiers, in order to look for appropriate accuracy-complexity trade-offs...
This paper considers a VRP with soft time windows and fuzzy demand (VRPTWFD). The objective is to minimize both the total distance covered by all vehicles as well as the sum of lateness at the customerpsilas due to the violation of time windows. This VRPTWFD is formulated as a two stages recourse model in the context of stochastic programming. The goal is then to minimize the expected cost, which...
In this article, a cooperative coevolutionary genetic algorithm for the solution of fuzzy vehicular routing problem (FVRP) is presented. FVRP is a variant of VRP with time windows; based on additional use of fuzzy due-times for customers' preferences. The objectives of FVRP are the minimization of total number of vehicles in service, total travel distance, and the total waiting time over all vehicles;...
With the intensification of market competition and fast development of science and technology, many enterprises have begun to realize the importance of logistic distribution vehicle routing problem under uncertainty environment, and begin to pay more attention to the research of this problem. In this paper, The traditional vehicle routing problem with time windows is expanded to the situation that...
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