Vasileios Zeimpekis

Real-time management of vehicle breakdowns in urban freight distribution

This paper considers a problem in which an unexpected event immobilises a vehicle of a distribution fleet permanently, and the remaining vehicles are rerouted to serve some of the clients of the failed vehicle. We model this case as a variation of the Team Orienteering Problem (TOP), constraining all vehicle routes to an upper time, or distance, limit, and taking into account the limited capacity of the fleet vehicles. The problem requires an effective solution in almost real time. We propose a new heuristic to provide efficient solutions within this strict computational time constraint. To test the quality of the heuristic, we have developed and validated a Genetic Algorithm (GA) that obtains high quality (but computationally expensive) solutions. The solutions of the heuristic compare favorably to those obtained by the GA. The latter has also been tested successfully in a real-time fleet management system.

Integrated planning in hybrid courier operations

Purpose – The purpose of this paper is to present the design and evaluation of an integrated system that supports planners and dispatchers to deliver enhanced courier operations. In addition to regular deliveries and pickups, these operations include: first, mass deliveries to be served over a horizon of multiple days; and second, real-time dynamic requests (DRs) to be served within the same service period. Design/methodology/approach – To address the aforementioned challenges, the authors developed an architecture that enhances a typical fleet management system by integrating purpose designed methods. Specifically, the authors plan mass deliveries taking into account typical routes of everyday operations. For planning DRs in real time, the authors propose an efficient insertion heuristic. Findings – The results from testing the proposed optimization algorithms for planning mass deliveries and real-time DRs are encouraging, since the proposed algorithms outperform current practices. Testing in a practical...

Data envelopment analysis models to support the selection of vehicle routing software for city logistics operations

In city logistics operations, vehicle routing is critical for successful freight delivery execution. Optimal routing, however, may not be performed when manual routing methods are implemented, due to their inability to cope with a number of delivery constraints such as hard delivery time windows. The use of an automated vehicle routing software by freight carriers, is usually the preferred option, as it may increase customer service and reduce operational costs. The evaluation and selection of automated routing software has become increasingly difficult for decision makers due to a large number of software products available and the great variety of features and capabilities they offer. This paper first develops a data model to capture all the significant attributes that characterize a routing software. The attributes are measured with ordinal data as they mainly express qualitative issues. Then, it presents a data envelopment analysis (DEA) model that aids the selection procedure by estimating the index Total Performance/Price that expresses the commonly used “value for money” criterion. This index is able to identify those routing software that are considered as best buys. Moreover, this paper proposes a DEA model to distinguish the best alternative from the “best buys” cases. A case study illustrates the proposed methodology.

Real-Time Fleet Management and Rerouting in City Logistics

The urban freight distribution is highly susceptible to unexpected events that often occur during delivery, such as delays at customer locations or due to traffic conditions. Such events may lead to inferior customer service, or higher costs, areas in which intelligent real-time fleet management may prove beneficial. In this paper, the authors present such a system that incorporates methods to estimate the expected travel time of a delivery vehicle, combining AVL-based real-time and historical data, with algorithms for efficient vehicle re-routings. The system continuously monitors the delivery process, detects possible delays in real-time, and adjusts the delivery schedule accordingly by suggesting effective re-routing strategies. The authors report results from testing the system via simulation and in a case study, and illustrate the extent of delivery performance improvements that may be achieved through such an approach.

A Transportation Planning Tool for Supporting Military Actions in Natural Disaster Relief Operations

Natural disasters such as flood, fire, earthquake, tornado and windstorm affect thousands of people every year. The involvement of the armed forces in disaster response and relief actions is critical as their role is primarily in response to the immediate requirement of human resources and technical equipment for rescue and relief operations of the affected area. Usually, a major type of assistance the military forces provide deals with the transportation of relief material. While commercial freight transport operations typically focus on minimizing costs, moving relief material is more concerned about satisfying demand for emergency supplies and saving lives. This task is particularly challenging given that emergency managers must operate under strict budget restrictions. To this end, this chapter presents the design, implementation and testing of a web tool that supports armed forces in freight transport planning during natural disaster relief operations. The proposed system is tested and the results show an increased performance in service provision with parallel reduction in administrative and transportation cost.