Port-IO: an integrative mobile cloud platform for real-time inter-terminal truck routing optimization

Abstract

Besides the transport of containers between transshipment areas, an increasing amount of containers needs to be moved to value-added logistics and auxiliary service areas leading to additional container flows within a seaport. Both real-time information exchange and optimization are necessary to efficiently coordinate actors and container movements being involved in respective inter-terminal transport (ITT). However, there is no decision support system facilitating real-time planning and management of ITT taking advantage of modern information technologies and optimization algorithms. In this paper, we formulate the inter-terminal truck routing problem as a novel optimization problem and propose two greedy heuristics and two hybrid simulated annealing algorithms. The computational experiments, conducted using real locations from the Port of Hamburg (Germany), are evaluated extensively. They indicate that the proposed hybrid simulated annealing algorithms are able to report feasible and improved routes within seconds. The optimization component is embedded into a scalable cloud platform that integrates both real-time data from truck drivers using a mobile app and current traffic data. As such, the proposed mobile cloud platform realizes the vision of a decision support system facilitating real-time communication and context-aware ITT planning for reducing costs and the carbon footprint.