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  • 1.
    Guajardo, Mario
    et al.
    NHH Norwegian School Econ, Norway .
    Kylinger, Martin
    Linköping University, Department of Management and Engineering, Production Economics. Linköping University, The Institute of Technology.
    Ronnqvist, Mikael
    NHH Norwegian School Econ, Norway .
    Joint optimization of pricing and planning decisions in divergent supply chain2013In: International Transactions in Operational Research, ISSN 0969-6016, E-ISSN 1475-3995, Vol. 20, no 6, p. 889-916Article in journal (Refereed)
    Abstract [en]

    In divergent supply chains, such as in the oil industry, processing raw materials results in an outflow of multiple products. Final products are stored at international depots, from where they are ready to be shipped to the markets. Even if one company controls the entire chain, when production and sales organizations are decoupled, a relevant problem is to determine the internal prices of products at depots for achieving coordination. We propose an optimization model involving pricing and production decisions, and several constraints commonly used in divergent chains. In our approach, the producer incorporates the sellers behavior by expressing demand as a function of the internal price. As a result, our model serves as a coordination mechanism in trying to get an overall coordinated integrated solution in a decoupled reality. Numerical examples in single and multiple periods problems show the advantages of our approach over cost-based methods.

  • 2.
    Karlsson, Jenny
    et al.
    Linköping University, Department of Mathematics. Linköping University, The Institute of Technology.
    Rönnqvist, Mikael
    Linköping University, Department of Mathematics. Linköping University, The Institute of Technology.
    Bergström, Johan
    The Forest Research Institute of Sweden, Uppsala, Sweden.
    Short-term harvest planning including scheduling of harvest crews2003In: International Transactions in Operational Research, ISSN 0969-6016, E-ISSN 1475-3995, Vol. 10, no 5, p. 413-431Article in journal (Refereed)
    Abstract [en]

    The problem we consider is short-term harvesting planning for a total planning period of 4–6 weeks where we want to decide the harvest sequences or schedules for harvest crews. A schedule is an order or sequence of harvest areas assigned to each crew. The harvesting of areas is planned in order to meet industrial demand. The total cost includes harvesting, transportation, and storage. One considerable cost is due to the quality reduction of logs stored at harvest areas. There are a number of restrictions to be considered. Areas are of varying size and the composition of assortments in each area is different. Each harvest team has different skills, a different home base, and different production capacity. Another aspect is the road network. There is a cost related to road opening (restoring, snow removal). In this paper, we develop a mixed integer programming (MIP) model for the problem. The schedules are represented by 0/1 variables. With a limited number of schedules, the problem can be solved by a commercial MIP solver. We have also developed a heuristic solution approach that provides high-quality integer solutions within a distinct time limit to be used when more schedules are used. Computational results from a major Swedish forest company are presented.

  • 3.
    Palmgren, Myrna
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Mathematics, Optimization .
    Rönnqvist, Mikael
    Linköping University, The Institute of Technology. Linköping University, Department of Mathematics, Optimization .
    Värbrand, Peter
    Linköping University, The Institute of Technology. Linköping University, Department of Science and Technology.
    A near-exact method for solving the log-truck scheduling problem2004In: International Transactions in Operational Research, ISSN 0969-6016, E-ISSN 1475-3995, Vol. 11, no 4, p. 447-464Article in journal (Refereed)
  • 4.
    Palmgren, Myrna
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Mathematics, Optimization .
    Rönnqvist, Mikael
    Linköping University, The Institute of Technology. Linköping University, Department of Mathematics, Optimization .
    Värbrand, Peter
    Linköping University, The Institute of Technology. Linköping University, Department of Science and Technology.
    A solution approach for log truck scheduling based on composite pricing and branch and bound2003In: International Transactions in Operational Research, ISSN 0969-6016, E-ISSN 1475-3995, Vol. 10, p. 433-447Article in journal (Refereed)
  • 5.
    Zhao, Yixin
    et al.
    Nanjing University of Science and Technology, School of Automation.
    Larsson, Torbjörn
    Linköping University, Department of Mathematics, Optimization . Linköping University, Faculty of Science & Engineering.
    Rönnberg, Elina
    Linköping University, Department of Mathematics, Optimization . Linköping University, Faculty of Science & Engineering.
    An integer programming column generation principlefor heuristic search methods2019In: International Transactions in Operational Research, ISSN 0969-6016, E-ISSN 1475-3995, Vol. 27, no 1, p. 665-695Article in journal (Refereed)
    Abstract [en]

    There is an increasing interest in integrating column generation and heuristic approaches to efficiently solve large-scale discrete optimisation problems. We contribute in this direction. Based on the insights from Lagrangian duality theory, we present an auxiliary problem that can be used for finding near-optimal solutions to a discrete column-oriented model. The structure of this auxiliary problem makes it suitable for being addressed with a heuristic search method involving column generation. To this end, we suggest a large neighbourhood search strategy where the repair step is to solve a column generation type subproblem. The suggested search strategy and mathematical models involved need to be tailored to the problem structure. To illustrate important design options and computational behaviour, four applications are studied: bin packing, generalised assignment, a resource allocation problem and the fixed-charge transportation problem.

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