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In this paper, the vehicle routing problem with time windows (VRPTW) was considered, and a mixed integer programming mathematic model of VRPTW was proposed in detail. Meantime, an improved ant colony algorithm (IACA) was proposed to overcome the shortcomings of premature convergence and slow convergence of conventional ant colony algorithm (ACA). The experiment results showed that the IACA can solve...
An important limitation of the fixed charge location model, is the assumption that full truckload quantities are shipped from a facility to a customer. In many contexts, shipments are made in less-than-truckload (LTL) quantities from a facility to customers along a multiple-stop route. The different location decision is made from the different cost of delivery. In this paper we are concerned with...
Logistics has received considerable attention recently due to the rapid technological development of electronics and the Internet. Normally, clients expect items to be delivered at times that are convenient for their own schedules. Therefore, a multi-objective problem (MOP) model that simultaneously considers the depot desires and clients expectations can better elucidate the real logistics operations...
Vehicle accidents are a major cause of death and claim more than 40,000 lives annually in the US alone. A substantial portion of these accidents occur at intersections. Stop signs and traffic signals are some of the intersection control devices used to increase safety and prevent collisions. However, these devices themselves can contribute to collisions, are costly, inefficient, and are prone to failure...
In this paper, the VRPTWRV (VRPTW with Re-used Vehicle) was presented and a mathematical programming model with multiple objects was constructed correspondingly. The heuristic information and Pseudo-random probability selection rule are improved according to the principle of serving customers with earlier service beginning time, shorter service time and earlier ending time firstly based on Ant Colony...
Sparse signal representations and approximations from overcomplete dictionaries have become an invaluable tool recently. In this paper, we develop a new, heuristic, graph-structured, sparse signal representation algorithm for overcomplete dictionaries that can be decomposed into subdictionaries and whose dictionary elements can be arranged in a hierarchy. Around this algorithm, we construct a methodology...
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