Efficient transportation logistics is crucial in society today. Yet, there is a large potential for improvement through better transportation planning. The optimal configuration of a transportation infrastructure, the design of optimal transportation routes for a "fleet" of lorries or ships, and the selection of best routes in a dynamic environment, are notable examples. Transportation planning tasks of some size are highly complex. By and large, they are still performed by human planners, unsupported by tools based on modern information and communication technology. There is a strong market demand for better tools. Lack of electronic shipment information, high quality geographical data, and industrial awareness have until recently been serious obstacles. Now, the performance of automated planning is the major bottleneck in the implementation of decision-support technology in transportation. The TOP programme aims at reducing the bottleneck through better optimization methods.
More efficient resolution of rich, optimization models of the applications at hand is the key to improvement. Due to their discrete nature and their structure, most important problems in transportation planning are computationally hard. Prime examples are variants of the so-called Travelling Salesperson Problem (TSP), the Vehicle Routing Problem (VRP), and network design problems. Methodological improvements are needed to effectively solve real-life transportation management problems under realistic response requirements. Adequate formulations must include side constraints, preferential constraints, and multiple objective criteria. Moreover, the co-ordination problem in practical transportation planning often is a non-trivial combination of several classical problems of Operations Research (OR) such as matching, routing, and resource allocation. For real-time planning, special techniques are needed to cater for problem dynamics.
In TOP, our goal is to develop better discrete optimisation methods to improve logistics performance in transportation. The foreseen results will enable resolution of real-life planning tasks that are beyond the scope of practical resolution today. First, TOP aims at effective resolution of large-size problem instances that are insoluble with current technology. Second, our goal is to develop planning technology that significantly improves performance in terms of plan quality versus response time. Such improvements are needed in order to develop better tools for automated decision-making at the strategic, tactical and operational levels. TOP results will meet unanswered requirements from the rapidly growing market for decision support tools in transportation logistics. This market is growing rapidly, in Norway, and in the rest of the world.
TOP enhances and complements a long-term strategic focus on applied optimization in transportation logistics at SINTEF Applied Mathematics. Strong research groups in applied optimization and geographical information technology have collaborated tightly in the build-up of leading-edge competence and technology in this area. These two groups performs the bulk of the work. There is collaboration with other strong research groups in applied discrete optimization, in Norway, and internationally. The Norwegian TOP network consists of (see also TOP Network):
The current contacts with the international scientific network is strengthened through workshops and visit from leading researchers.
Selected results in the form of better optimization techniques for key problems will be implemented in the SPIDER software library. Hence, they will be commercialised through the Norwegian software vendor GreenTrip AS and others. As a contract research institute, SINTEF shall exploit the enhanced knowledge through acquisition of new, industrial RTD contracts in applied optimization. When implemented in industry, we expect TOP results to have significant impacts on economy and the environment. Results from TOP will be published in academic journals, and further disseminated via articles in polytechnic magazines, workshops and seminars. The TOP web site has been established also to make benchmarks and results available to the research community. More than that, the TOP web pages constitute a central web resource for the international research community in transport optimization.
The programme is organised as a research action over 4 years, including 1-2 PhD scholarships at NTNU and a part-time position at the University of Oslo to increase the number of Norwegian graduates in computational logistics, as well as funds for visits from highly reputed researchers in the field. To focus research efforts, we have selected three key problems where enhanced optimization capabilities will have a large impact on overall logistics performance:
Our general methodological approach will be to:
Hybrid methods, combining local search, meta-heuristics, constraint propagation, and exact methods will be investigated in TOP.
TOP builds upon results from earlier work in industrial and strategic projects. It is closely co-ordinated with several relevant, ongoing projects funded by industry, the Research Council of Norway, the European Commission, as well as internally funded strategic projects.
The total TOP budget is 13.4 MNOK, including funding for 1-2 PhDs and visiting researcher stays.
See also presentations from first TOP Users Forum meeting and first meeting in the Norwegian TOP Network.
Created July 20 2001 by amr
Last Updated November 13 2001 by gha