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RuttOpt – A decision support system for routing of logging trucks

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    We describe the decision support system RuttOpt, which is developed for scheduling logging trucks in the Swedish forest industry. The system is made up of a number of modules. One module is the Swedish road database NVDB which consists of detailed information of all the roads in Sweden. This also includes a tool to compute distances between locations. A second module is an optimization routine that finds a schedule i.e. set of routes for all trucks. This is based on a two phase algorithm where Linear Programming and a standard tabu search method are used. A third module is a database, storing all relevant information. At the heart of the system is a user interface where information and results can be viewed on maps, Gantt schedules and result reports. We also describe the characteristics of the general routing problem in forestry together with a focus on the planning process and systems in use in the Swedish situation. The system RuttOpt has been used in a number of case studies and we describe four of these. The case studies have been made in both forest companies and hauling companies. The cases range from ten to 110 trucks and with a planning horizon ranging from between one and five days. The results show that the system can be used to solve large case studies and that the potential savings are in the range 5-30%.

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    Paper provided by Department of Business and Management Science, Norwegian School of Economics in its series Discussion Papers with number 2007/16.

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    Length: 34 pages
    Date of creation: 06 Jul 2007
    Handle: RePEc:hhs:nhhfms:2007_016
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    NHH, Department of Business and Management Science, Helleveien 30, N-5045 Bergen, Norway

    Phone: +47 55 95 92 93
    Fax: +47 55 95 96 50
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    1. Flisberg, Patrik & Lidén, Bertil & Rönnqvist, Mikael, 2007. "A hybrid method based on linear programming and tabu search for routing of logging trucks," Discussion Papers 2007/14, Department of Business and Management Science, Norwegian School of Economics.
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