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  • 1.
    Dhak, Janice
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Dahlquist, Erik
    Mälardalen University, Department of Mathematics and Physics.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    Ruiz, Jean
    Mälardalen University, Department of Mathematics and Physics.
    Generic methods for paper mill optimisation2004In: PTS-COST Symposium Simulation and Process Control for the Paper Industry, (Munchen, Germany, March 9-10, 2004), 2004Conference paper (Refereed)
  • 2.
    Dhak, Janice
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Dahlquist, Erik
    Mälardalen University, Department of Mathematics and Physics.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    Ruiz, Jean
    Centre Technique du Papier, Domaine Universitaire, France.
    Belle, Jurgen
    Papiertechnische Stiftung, Germany.
    Goedsch, Frank
    Papiertechnische Stiftung, Germany.
    Developing a generic method for paper mill optimization2004In: Proceedings of the PAPTAC Control Systems 2004 Conference, (Quebec City, Canada, June 14-18), 2004, p. 207-214Conference paper (Refereed)
    Abstract [en]

    A generic method for formulating pulp and paper optimization problems is presented. Two ongoing projects in the framework of the DOTS project illustrate the method: optimization of sizing quality at a specialty paper mill, and optimization of the water and broke systems at a coated paper mill. Explicit and implicit formulations are compared, and different usages of external simulators in conjunction with optimization are discussed. The problems are solved using MATLAB/TOMLAB. Some results from different optimization algorithms are also presented.

  • 3.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    A Global Optimization Approach for Integrated Design and Parameter Estimation in Process Engineering2006Other (Other academic)
  • 4.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    An adaptive radial basis algorithm (ARBF) for expensive black-box global optimization2008In: Journal of Global Optimization, ISSN 1573-2916, Vol. 41, no 3, p. 447-464Article in journal (Refereed)
    Abstract [en]

    Powerful response surface methods based on kriging and radial basis function (RBF) interpolation have been developed for expensive, i.e. computationally costly, global nonconvex optimization. We have implemented some of these methods in the solvers rbfSolve and EGO in the TOMLAB Optimization Environment (http://www.tomopt.com/tomlab/). In this paper we study algorithms based on RBF interpolation. The practical performance of the RBF algorithm is sensitive to the initial experimental design, and to the static choice of target values. A new adaptive radial basis interpolation (ARBF) algorithm, suitable for parallel implementation, is presented. The algorithm is described in detail and its efficiency is analyzed on the standard test problem set of Dixon-Szego. Results show that it outperforms the published results of rbfSolve and several other solvers.

  • 5.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    An Adaptive Radial Basis Algorithm (ARBF) for Expensive Black-Box Mixed-Integer Constrained Global Optimization2005In: Conference on Least Squares and Optimization: In honour of professor Per-Åke Wedin, Umeå University, November 16-17, 2005, 2005Conference paper (Refereed)
  • 6.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    An Adaptive Radial Basis Algorithm (ARBF) for Mixed-Integer Expensive Constrained Global Optimization2005In: Proceedings of the International Workshop on Global Optimization: San Jose, Almeria, Spain, September 18-22, 2005, 2005, p. 133-140Conference paper (Refereed)
  • 7.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    Mixed-integer expensive global optimization with TOMLAB2004Conference paper (Other academic)
  • 8.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    Nonlinear Systems Modeling and Optimization: State-of-Art and Perspectives: Panel presentation2006In: EURO XXI, 21th European Conference on Operational Research, Reykavik, Iceland, July 2-5, 2006: OR for Better Management of Sustainable Development, 2006Conference paper (Refereed)
  • 9.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    Radial Basis Algorithms for Expensive Derivative-Free Black-Box Mixed-Integer Constrained Global Optimization2007In: Conference Proceeding GOR Workshop on Global Optimization: 79th Meeting of the GOR Working Group, Physikzentrum, Bad Honnef, 18-19 October 2007, 2007Conference paper (Refereed)
  • 10.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    TOMLAB - Unique Features for Advanced Optimization in MATLAB2006Other (Other academic)
  • 11.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    TOMLAB - Unique Features for Optimization in MATLAB2004Conference paper (Refereed)
  • 12.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Edvall, Marcus
    Göran, Anders
    Daily Milk Cow Feed Optimization in the Nordic Countries with TOMLAB2006In: EURO XXI, 21th European Conference on Operational Research, Reykavik, Iceland, July 2-5, 2006: OR for Better Management of Sustainable Development, 2006Conference paper (Refereed)
  • 13.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Edvall, Marcus
    Göran, Anders
    TOMLAB - Large-Scale Optimization in MATLAB, LABVIEW and .NET2007In: ICCOPT II & MOPTA-07, 2nd Mathematical Programming Society International Conference on Continuous Optimization: McMaster University, Hamilton, Canada, August 12-16, 2007, 2007Conference paper (Refereed)
  • 14.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Edvall, Marcus M.
    Mälardalen University, Department of Mathematics and Physics.
    The TOMLAB optimization environment2004Licentiate thesis, monograph (Other scientific)
  • 15.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Edvall, Marcus M.
    Mälardalen University, Department of Mathematics and Physics.
    THE TOMLAB OPTIMIZATION ENVIRONMENT2004In: Modeling Languages in Mathematical Optimization, Kluwer Academic Publishers, 2004, p. 369-376Chapter in book (Refereed)
  • 16.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Edvall, Marcus M.
    Göran, Anders
    Mixed-Integer expensive constrained global optimization with TOMLAB2005In: The eight SIAM conference about Optimization: Stockholm, May 15-19, 2005, 2005Conference paper (Refereed)
  • 17.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Edvall, Marcus M.
    Mälardalen University, Department of Mathematics and Physics.
    Göran, Anders
    Mälardalen University, Department of Mathematics and Physics.
    Tomlab - For Large-Scale Robust Optimization2003In: Proceedings for the Nordic Matlab Conference, 2003Conference paper (Other scientific)
  • 18.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Göran, Anders
    Mälardalen University, Department of Mathematics and Physics.
    User's Guide for Tomlab v3.2.12002Report (Other academic)
  • 19.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Kocjan, Waldemar
    Mälardalen University, Department of Mathematics and Physics.
    AUTOPACK - Algorithms for Automated Container Loading2008In: Journal of Numerical and Applied Mathematics, ISSN 0868-6912, Vol. 96, no 1, p. 105-118Article in journal (Refereed)
    Abstract [en]

    The container loading problem aims at optimal packing of boxes of different dimensions into available containers with respect to some objective function. This problem arises in areas like distribution and logistics. Since the scale of distribution and amount of distributed goods grows rapidly, so does the need for more energy effective and environmentally friendly distribution methods.This paper  considers a single container loading problem motivated by a real life application. The formulation includes an objective function for maximizing utilization of a container and additional constraints such as a predefined order and priorities between boxes. A short evaluation of the algorithm is presented as well as some directions for future development.

  • 20.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Kocjan, Waldemar
    Mälardalen University, School of Education, Culture and Communication.
    Generating Stable Loading Patterns for Pallet Loading Problems2008In: First Workshop on Bin Packing and Placement Constraints (BPPC’08), 2008, p. 1-6Conference paper (Refereed)
  • 21.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Lasdon, Leon
    Mälardalen University, Department of Mathematics and Physics.
    Pintér, János D.
    Mälardalen University, Department of Mathematics and Physics.
    Shoemaker, Christine
    Mälardalen University, Department of Mathematics and Physics.
    Ugray, Zsolt
    Mälardalen University, Department of Mathematics and Physics.
    Advanced global optimization – Scientific and engineering applications2004Conference paper (Other academic)
  • 22.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Quttineh, Nils-Hassan
    Mälardalen University, Department of Mathematics and Physics.
    Radial Basis Algorithms for Mixed-Integer Expensive Constrained Global Optimization2006In: Second International Workshop on SURROGATE MODELLING AND SPACE MAPPING FOR ENGINEERING OPTIMIZATION: SMSMEO-06, Copenhagen, Denmark, November 9-11, 2006, 2006Conference paper (Refereed)
  • 23.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Quttineh, Nils-Hassan
    Mälardalen University, School of Education, Culture and Communication.
    The influence of different Experimental Designs on the performance of Surrogate Model based Costly Global Optimization Solvers2008Conference paper (Refereed)
  • 24.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Quttineh, Nils-Hassan
    Mälardalen University, School of Education, Culture and Communication.
    The influence of Experimental Designs on the Performance of Surrogate Model Based Costly Global Optimization Solvers2009In: Studies in Informatics and Control, ISSN 1220-1766, E-ISSN 1841-429X, Vol. 18, no 1, p. 87-95Article in journal (Refereed)
    Abstract [en]

    When dealing with costly objective functions in optimization, one good alternative is to use a surrogate model approach. A common feature for all such methods is the need of an initial set of points, or "experimental design", in order to start the algorithm. Since the behavior of the algorithms often depends heavily on this set, the question is how to choose a good experimental design. We investigate this by solving a number of problems using different designs, and compare the outcome with respect to function evaluations and a root mean square error test of the true function versus the surrogate model produced. Each combination of problem and design is solved by 3 different solvers available in the TOMLAB optimization environment. Results indicate two designs as superior.

  • 25.
    Holmström, Kenneth
    et al.
    Mälardalen University. Mälardalen University, Department of Mathematics and Physics.
    Quttineh, Nils-Hassan
    Mälardalen University. Mälardalen University, School of Education, Culture and Communication.
    Edvall, Marcus
    Tomlab Optimization Inc..
    Adaptive Radial Basis Algorithms (ARBF) for Expensive Black-Box Global MINLP Optimization2008In: SIOPT08 - SIAM Optimization, Boston, USA, 2008Conference paper (Refereed)
    Abstract [en]

    Parallel implementations of the adaptive radial basis function algorithm (ARBF)for computationally costly optimization are presented.Modifications of  ARBF to improve robustness and speed are discussed.The algoritm is implemented in solver PARFMIP in the TOMLAB Optimization Environment (http://tomopt.com/). Solvers in TOMLAB are used to solve global and local subproblems.Results and comparisons with other solvers are presentedfor a large set of global optimization test problems.Performance on some costly real-life applications are reported.

  • 26.
    Holmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Quttineh, Nils-Hassan
    Mälardalen University, School of Education, Culture and Communication.
    Edvall, Marcus
    Tomlab Optimization Inc..
    An adaptive radial basis algorithm (ARBF) for expensive black-box mixed-integer constrained global optimization2008In: Optimization and Engineering, ISSN 1389-4420, E-ISSN 1573-2924, Vol. 9, no 4, p. 311-339Article in journal (Refereed)
    Abstract [en]

    Response surface methods based on kriging and radial basis function (RBF) interpolationhave been successfully applied to solve expensive, i.e. computationally costly,global black-box nonconvex optimization problems.In this paper we describe extensions of these methods to handle linear, nonlinear, and integer constraints. In particular, algorithms for standard RBF and the new adaptive RBF (ARBF) aredescribed. Note, however, while the objective function may be expensive, we assume that any nonlinear constraints are either inexpensive or are incorporated into the objective function via penalty terms. Test results are presented on standard test problems, both nonconvexproblems with linear and nonlinear constraints, and mixed-integernonlinear problems (MINLP). Solvers in the TOMLAB OptimizationEnvironment (http://tomopt.com/tomlab/) have been compared,specifically the three deterministic derivative-free solversrbfSolve, ARBFMIP and EGO with three derivative-based mixed-integernonlinear solvers, OQNLP, MINLPBB and MISQP, as well as the GENOsolver implementing a stochastic genetic algorithm. Results showthat the deterministic derivative-free methods compare well with thederivative-based ones, but the stochastic genetic algorithm solver isseveral orders of magnitude too slow for practical use.When the objective function for the test problems is costly to evaluate, the performance of the ARBF algorithm proves to be superior.

  • 27.
    Hoolmström, Kenneth
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Quttineh, Nils-Hassan
    Mälardalen University, Department of Mathematics and Physics.
    An Adaptive Radial Basis Algorithm (ARBF) for Expensive Black-Box Mixed-Integer Constrained Global Optimization2006In: EURO XXI, 21th European Conference on Operational Research, Reykavik, Iceland, July 2-5, 2006: OR for Better Management of Sustainable Development, 2006Conference paper (Refereed)
  • 28.
    Häggstål, Daniel
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Kvarnström, Andreas
    Mälardalen University, Department of Mathematics and Physics.
    Dotzauer, Erik
    Mälardalen University, Department of Mathematics and Physics.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    Fuel mix optimization of combined heat and power production utilizing a simulation model2004Conference paper (Refereed)
  • 29.
    Kocjan, Waldemar
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Holmström, Kenneth
    Mälardalen University, School of Innovation, Design and Engineering.
    Computing stable loads for pallets2010In: European Journal of Operational Research, ISSN 0377-2217, E-ISSN 1872-6860, Vol. 207, no 2, p. 980-985Article in journal (Refereed)
    Abstract [en]

    This paper describes an Integer Programming model for generating stable loading patterns for the Pallet Loading Problem under several stability criteria. The results obtained during evaluation show great improvement in the number of stable patterns in comparison with results reported earlier. Moreover, most of the solved cases also ensure optimality in terms of utilization of a pallet.

  • 30.
    Kocjan, Waldemar
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    Mathematical Models for Automated Container Loading - an Introductory Study.: Optimization of Packaging with Robots2006Conference paper (Other academic)
  • 31.
    Kocjan, Waldemar
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    The AUTOPACK Project - Algorithms for Container Loading2006Report (Other academic)
  • 32.
    Käck, Jan-Erik
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    Constrained Global Optimization with Radial Basis Functions2003Report (Other academic)
    Abstract [en]

    Response surface methods show promising results for global optimization of costly non convex objective functions, i.e. the problem of finding the global minimum when there are several local minima and each function value takes considerable CPU time to compute. Such problems often arise in industrial and financial applications, where a function value could be a result of a time-consuming computer simulation or optimization. Derivatives are most often hard to obtain. The problem is here extended with linear and nonlinear constraints, and the nonlinear constraints can be costly or not. A new algorithm that handles the constraints, based on radial basis functions (RBF), and that preserves the convergence proof of the original RBF algorithm is presented. The algorithm takes advantage of the optimization algorithms in the Tomlab optimization environment (www.tomlab.biz). Numerical results are presented for standard test problems.

  • 33.
    Quttineh, Nils-Hassan
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    Adaptive Radial Basis Algorithms (ARBF) for Expensive Black-Box Mixed-Integer Constrained Global Optimization2007Conference paper (Refereed)
  • 34.
    Ritala, Risto
    et al.
    Mälardalen University, Department of Mathematics and Physics.
    Belle, Jurgen
    Mälardalen University, Department of Mathematics and Physics.
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    Ihalainen, Heimo
    Mälardalen University, Department of Mathematics and Physics.
    Ruiz, Jean
    Mälardalen University, Department of Mathematics and Physics.
    Suojarvi, Mika
    Mälardalen University, Department of Mathematics and Physics.
    Tienari, Matti
    Mälardalen University, Department of Mathematics and Physics.
    Operations Decision Support based on Dynamic Simulation and Optimization2004In: Proceedings of the PulPaper 2004 Effiency Conferencen, Helsinki Finland, 2004Conference paper (Other academic)
  • 35. Ritala, Risto
    et al.
    Belle, Jurgen
    Holmström, Kenneth
    Mälardalen University, Department of Mathematics and Physics.
    Ihalainen, Heimo
    Ruiz, Jean
    Suojärvi, Mika
    Tienari, Matti
    Mälardalen University, Department of Mathematics and Physics.
    Operations decision support based on dynamic simulation and optimization2004In: Proceedings of the PulPaper 2004 Efficiency Conference, The Finnish Paper Engineers' Association, (Helsinki, Finland, June 1-4), 2004Conference paper (Refereed)
1 - 35 of 35
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