In this paper we present a formulation for the dynamic vehicle routing problem with time-dependent travel times. We also present a genetic algorithm to solve the problem. The problem is a pick-up or delivery vehicle routing problem with soft time …
In the standard version of the traveling salesman problem (TSP), we are given a set of customers located in and around a city and the distances between each pair of customers, and need to find the shortest tour that visits …
This work addresses the problem of determining optimal routing decisions in signalized traffic networks, where arc travel times vary over time and are known only probabilistically (i.e. in stochastic, time-varying (STV) networks) and additional delay due to signal operations is …
In this article, we propose a solution procedure for the Elementary Shortest Path Problem with Resource Constraints (ESPPRC). A relaxed version of this problem in which the path does not have to be elementary has been the backbone of a …
With the increasing availability of real-time information and communication systems in logistics, the need for appropriate planning algorithms, which make use of this technology, arises. Customers in transport markets increasingly expect quicker and more flexible fulfillment of their orders, especially …
Models and algorithms for vehicle routing are usually based on known constant travel times between all relevant locations, an assumption that is far from reality, particularly for urban areas. But the consideration of travel times that vary with the time …
Most of the models for vehicle routing reported in the literature assume constant travel times. Clearly, ignoring the fact that the travel time between two locations does not depend only on the distance traveled, but on many other factors including …
Travel times in congested transportation networks are time-varying quantities that can at best be known a priori probabilistically. In such networks, the arc weights (travel times) are represented by random variables whose probability distribution functions vary with time. These networks …
The existing dynamic and stochastic shortest path problem (DSSPP) algorithms assume that the mean and variance of link travel time (or other specific random variable such as cost) are available. When they are used with observed data from previous time …
Previous literature on the Traveling Salesman Problem (TSP) assumed that the sites to be visited are stationary. Motivated by practical applications, we introduce a time-dependent generalization of TSP which we call Moving-Target TSP, where a pursuer must intercept in minimum …