Collab

Advanced vehicle routing and route finding tools are increasingly being used for more efficient transportation. Their effect is largely determined by a combination of the power of the underlying optimization methods and the power of the computer. For many applications, there is still a large gap between performance requirements and the performance offered by tools.

High-performance transportation optimization through parallel and collaborative methods

Date

09/200907/2012. Project ended.

Funding

Research Council of Norway

Coordinating site

SINTEF

Partners

  • the Optimization and Heterogeneous Computing groups of SINTEF ICT, Oslo, Norway
  • The Dolphin Group, INRIA Lille, France
  • CIRRELT, Montreal, Canada
  • ITMMA, University of Antwerp, Belgium

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In collaboration with research groups abroad, SINTEF has developed highly competitive methods for rich, industrial variants of the Vehicle Rout ing Problem and the Dynamic Shortest Path Problem. The methods have been implemented in vehicle routing and route finding tools, e.g., the Spider technology, and disseminated to industry through vendors. Hence, they improve transportation efficiency in ma ny organizations.

Until recently, the performance of transportation optimization software has increased rapidly through a combination of research based improvement of optimization methods and the general increase of CPU clock frequency. The latter has stag nated due to technological limits. Increasing power is now instead offered through an increasing number of cores. Graphics processors (GPUs) become more programmable and show a drastic increase of performance for data-parallel computing. In the near futur e, commodity processors will be heterogeneous and combine a high number of cores and programmable GPUs. To exploit these developments, it is now absolutely necessary that new and parallelized transportation optimization methods are developed.

In COLLAB, w e develop new parallel and collaborative optimization methods, starting from existing, high performance methods. The methods will fully utilize current multi-core and heterogeneous hardware platforms, and automatically benefit from the future performance increase of such platforms. The COLLAB consortium consists of the Optimization and Heterogeneous Computing groups of SINTEF, plus three renowned research groups in parallel computing, discrete optimization, and transportation from abroad. One postdoc has been employed at SINTEF.

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