Evaluation of an expanded satellite based mobile communications tracking system

Since the terrorist events in the United States on September 11, 2001, the Federal Motor Carrier Safety Administration has been testing and evaluating cargo tracking technologies to improve the safety, security, and efficiency of commercial motor vehicle operations. While satellite-based systems used for tracking vehicles and cargo provide sufficient geographic coverage in the majority of the United States, there remain several vital regions that are uncovered and difficult to monitor. One such region is Alaska, where officials arc particularly concerned with the hazardous materials shipments that are transported parallel to the Trans-Alaska Pipeline. This article analyzes the risks and benefits associated with adopting an Expanded Satellite-Based Mobile Communications Tracking System to monitor hazardous materials and high-value cargo in Alaska. Technical and acceptance risks are evaluated against the communication, safety, security and real time information benefits that the system provides. The findings indicate that the system provides a significant communications upgrade relative to previously available technology

Algorithm Engineering in Robust Optimization

Robust optimization is a young and emerging field of research having received a considerable increase of interest over the last decade. In this paper, we argue that the the algorithm engineering methodology fits very well to the field of robust optimization and yields a rewarding new perspective on both the current state of research and open research directions. To this end we go through the algorithm engineering cycle of design and analysis of concepts, development and implementation of algorithms, and theoretical and experimental evaluation. We show that many ideas of algorithm engineering have already been applied in publications on robust optimization. Most work on robust optimization is devoted to analysis of the concepts and the development of algorithms, some papers deal with the evaluation of a particular concept in case studies, and work on comparison of concepts just starts. What is still a drawback in many papers on robustness is the missing link to include the results of the experiments again in the design

A pickup and delivery problem using crossdocks and truckload lane rates

This paper presents solution approaches for a shipper pickup and delivery planning problem to move freight from suppliers to distribution centers. Each shipment is moved either direct via a less-than-truckload (LTL) carrier, or possibly consolidated with other shipments and moved by one or two truckload (FTL) routes. When using a FTL carrier, the shipper takes advantage of contracted lane rates that establish prices per mile for a truck operated between two locations that are significantly less than the comparable LTL price for shipping a full truckload. The challenge for the shipper is to consolidate multiple shipments effectively to take advantage of this price differential. Consolidated FTL routes may each visit multiple shipment origins (supplier locations) and/or destinations (distribution center locations). Additionally, FTL routes may move shipments through a single crossdock facility en route. A path-based integer programming model for this planning problem is presented. The model can be solved directly with commercial integer programming software for smaller instances. For larger instances, a search scheme is developed in which restrictions to the integer program are solved sequentially. A computational study using data from a major US retailer demonstrates the effectiveness of the solution approaches. In each instance, substantial transportation cost savings are identified from baseline LTL costs