Cargo Consolidation and Distribution Through a Terminals-Network: A Branch-And-Price Approach

Less-than-truckload is a transport modality that includes many practical variations to convey a number of transportation-requests from the origin locations to their destinations by using the possibility of goods-transshipments on the carrier?s terminals-network. In this way logistics companies are required to consolidate shipments from different suppliers in the outbound vehicles at a terminal of the network. We present a methodology for finding near-optimal solutions to a less-than-truckload shipping modality used for cargo consolidation and distribution through a terminals-network. The methodology uses column generation combined with an incomplete branch-and-price procedure.Fil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentin

RESOURCE ALLOCATION AND EFFICIENT ROUTING IN WIRELESS NETWORKS

In wireless networks, devices (nodes) are connected by wireless links. An important issue is to set up high quality (high bandwidth) and efficient routing paths when one node wants to send packets to other nodes. Resource allocation is the foundation to guarantee high quality connections. In addition, it is critical to handle void areas in order to set up detour-free paths. Moreover, fast message broadcasting is essential in mobile wireless networks. Thus, my research includes dynamic channel allocation in wireless mesh networks, geographic routing in Ad Hoc networks, and message broadcasting in vehicular networks. The quality of connections in a wireless mesh network can be improved by equip- ping mesh nodes with multi-radios capable of tuning to non-overlapping channels. The essential problem is how to allocate channels to these multi-radio nodes. We develop a new bipartite-graph based channel allocation algorithm, which can improve bandwidth utilization and lower the possibility of starvation. Geographic routing in Ad Hoc networks is scalable and normally loop-free. However, traditional routing protocols often result in long detour paths when holes exist. We propose a routing protocol-Intermediate Target based Geographic Routing (ITGR) to solve this problem. The novelty is that a single forwarding path can be used to reduce the lengths of many future routing paths. We also develop a protocol called Hole Detection and Adaptive Geographic Routing, which identifies the holes efficiently by comparing the length of a routing path with the Euclidean distance between a pair of nodes. We then set up the shortest path based on it. Vehicles play an important role in our daily life. During inter-vehicle communication, it is essential that emergency information can be broadcast to surrounding vehicles quickly. We devise an approach that can find the best re-broadcasting node and propagate the message as fast as possible

Dynamic Vehicle Routing for Robotic Systems

Recent years have witnessed great advancements in the science and technology of autonomy, robotics, and networking. This paper surveys recent concepts and algorithms for dynamic vehicle routing (DVR), that is, for the automatic planning of optimal multivehicle routes to perform tasks that are generated over time by an exogenous process. We consider a rich variety of scenarios relevant for robotic applications. We begin by reviewing the basic DVR problem: demands for service arrive at random locations at random times and a vehicle travels to provide on-site service while minimizing the expected wait time of the demands. Next, we treat different multivehicle scenarios based on different models for demands (e.g., demands with different priority levels and impatient demands), vehicles (e.g., motion constraints, communication, and sensing capabilities), and tasks. The performance criterion used in these scenarios is either the expected wait time of the demands or the fraction of demands serviced successfully. In each specific DVR scenario, we adopt a rigorous technical approach that relies upon methods from queueing theory, combinatorial optimization, and stochastic geometry. First, we establish fundamental limits on the achievable performance, including limits on stability and quality of service. Second, we design algorithms, and provide provable guarantees on their performance with respect to the fundamental limits.United States. Air Force Office of Scientific Research (Award FA 8650-07-2-3744)United States. Army Research Office. Multidisciplinary University Research Initiative (Award W911NF-05-1-0219)National Science Foundation (U.S.) (Award ECCS-0705451)National Science Foundation (U.S.) (Award CMMI-0705453)United States. Army Research Office (Award W911NF-11-1-0092

Stochastic Dynamic Vehicle Routing in the Euclidean Plane: The Multiple-Server, Capacitated Vehicle Case

In a previous paper [12], we introduced a new model for stochastic and dynamic vehicle routing called the dynamic traveling repairman problem (DTRP), in which a vehicle traveling at constant velocity in a Euclidean region must service demands whose time of arrival, location and on-site service are stochastic. The objective is to find a policy to service demands over an infinite horizon that minimizes the expected system time (wait plus service) of the demands. We showed that the stability condition did not depend on the geometry of the service region (i.e. size, shape, etc.). In addition, we established bounds on the optimal system time and proposed an optimal policy in light traffic and several policies that have system times within a constant factor of the lower bounds in heavy traffic. We showed that the leading behavior of the optimal system time had a particularly simple form which increases much more rapidly with traffic intensity than the system time in traditional queues (e.g. M/G/1). In this paper, we extend these results in several directions. First, we propose new bounds and policies for the problem of m identical vehicles with unlimited capacity and show that in heavy traffic the system time is reduced by a factor of 1/m2 over the single server case. Policies based on dividing the service region into m equal subregion