I. Minis, K. Mamasis, V. Zeimpekis

 Journal of Heuristics, vol.18, n.3, 2012, 375-400

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.

Th. Athanasopoulos, I. Minis

In book I. Minis, V. Zeimpekis, G. Dounias, N. Ampazis (Eds.), Supply Chain Optimization, Design & Management: Advances & Intelligent Methods, IGI Global Publications, Chapter 11, 232 – 251, 2011.

Appointment-based logistics systems, such as special courier services, or repair / maintenance services, face ever increasing competitive pressures for efficiency and on-time performance. For example, in addition to typical (core) operations, courier service providers lately deal with micrologistics activities, such as bulk product deliveries. The promise dates of such deliveries have some flexibility within a pre-specified service level. In this hybrid environment, bulk deliveries are typically planned on an ad hoc basis, without taking explicitly into account the workload for core operations, a practice that may lead to inefficiencies. This chapter proposes a new method to perform assignment of service requests (calls) with some flexibility taking into account expected routes in a multi-period horizon. The problem is solved on a rolling horizon basis in order to address the dynamics of arriving calls. The method is tested through several theoretical examples, as well as in an extensive industrial case, and appears to be superior to current methods used in practice.