DESSLib – Benchmark Instances for Optimization of Decentralized Energy Supply Systems

  • Fritz Arnold
  • Björn Bahl
  • André Bardow
  • Arie M.C.A. Koster
  • Marco E. Lübbecke
  • Sebastian Goderbauer
  • Philip Voll
    • Categories Applications - Science and Engineering Tags , , , , , ,

    DESSLib (http://www.math2.rwth-aachen.de/DESSLib) provides benchmark instances obtained by real world data for synthesis problems of decentralized energy supply systems (DESS). In this paper, the considered optimization problem is described in detail. For a description of the functions and parameters used to describe the system and equipment, see the documentation found on DESSLib website http://www.math2.rwth-aachen.de/DESSLib. ArticleDownload View … Read more

    An Adaptive Discretization MINLP Algorithm for Optimal Synthesis of Decentralized Energy Supply Systems

  • Björn Bahl
  • André Bardow
  • Arie M.C.A. Koster
  • Marco E. Lübbecke
  • Sebastian Goderbauer
  • Philip Voll
    • Categories (Mixed) Integer Nonlinear Programming, Applications - Science and Engineering Tags , , , ,

    Decentralized energy supply systems (DESS) are highly integrated and complex systems designed to meet time-varying energy demands, e.g., heating, cooling, and electricity. The synthesis problem of DESS addresses combining various types of energy conversion units, choosing their sizing and operations to maximize an objective function, e.g., the net present value. In practice, investment costs and … Read more

    Multi-Period Portfolio Optimization: Translation of Autocorrelation Risk to Excess Variance

  • Byung-Geun Choi
  • Ruiwei Jiang
  • Napat Rujeerapaiboon
    • Categories Finance and Economics, Robust Optimization, Stochastic Programming Tags , , ,

    Growth-optimal portfolios are guaranteed to accumulate higher wealth than any other investment strategy in the long run. However, they tend to be risky in the short term. For serially uncorrelated markets, similar portfolios with more robust guarantees have been recently proposed. This paper extends these robust portfolios by accommodating non-zero autocorrelations that may reflect investors’ … Read more

    Convergence Analysis of ISTA and FISTA for “Strongly + Semi” Convex Programming

  • Ke Guo
  • Xiao-Ming Yuan
  • Shangzhi Zeng
    • Categories Convex Optimization Tags , , , , ,

    The iterative shrinkage/thresholding algorithm (ISTA) and its faster version FISTA have been widely used in the literature. In this paper, we consider general versions of the ISTA and FISTA in the more general “strongly + semi” convex setting, i.e., minimizing the sum of a strongly convex function and a semiconvex function; and conduct convergence analysis … Read more

    On cone based decompositions of proper Pareto optimality

  • Marlon Braun
  • Hartmut Schmeck
  • Pradyumn Kumar Shukla
    • Categories Global Optimization, Multi-Criteria Optimization Tags , , ,

    In recent years, the research focus in multi-objective optimization has shifted from approximating the Pareto optimal front in its entirety to identifying solutions that are well-balanced among their objectives. Proper Pareto optimality is an established concept for eliminating Pareto optimal solutions that exhibit unbounded tradeo ffs. Imposing a strict tradeo ff bound allows specifying how many units … Read more

    An exact hybrid method for the vehicle routing problem with time windows and multiple deliverymen

  • Aldair Álvarez
  • Pedro Munari
    • Categories Combinatorial Optimization, Transportation

    The vehicle routing problem with time windows and multiple deliverymen (VRPTWMD) is a variant of the vehicle routing problem with time windows in which service times at customers depend on the number of deliverymen assigned to the route that serves them. Hence, in addition to the usual routing and scheduling decisions, the crew size for … Read more

    Inexact Newton-Type Optimization with Iterated Sensitivities

  • Moritz Diehl
  • Sebastien Gros
  • Rien Quirynen
    • Categories Systems governed by Differential Equations Optimization Tags , , ,

    This paper presents and analyzes an Inexact Newton-type optimization method based on Iterated Sensitivities (INIS). A particular class of Nonlinear Programming (NLP) problems is considered, where a subset of the variables is defined by nonlinear equality constraints. The proposed algorithm considers an arbitrary approximation for the Jacobian of these constraints. Unlike other inexact Newton methods, … Read more

    The proximal point method for locally Lipschitz functions in multiobjective optimization

  • Glaydston Bento
  • João Xavier da Cruz Neto
  • Antoine Soubeyran
  • João Carlos Souza
  • G. López
    • Categories Applications - OR and Management Sciences, Multi-Criteria Optimization Tags , , , , ,

    This paper studies the constrained multiobjective optimization problem of finding Pareto critical points of vector-valued functions. The proximal point method considered by Bonnel et al. (SIAM J. Optim., 4 (2005), pp. 953-970) is extended to locally Lipschitz functions in the finite dimensional multiobjective setting. To this end, a new approach for convergence analysis of the … Read more

    Efficient Subgradient Methods for General Convex Optimization

  • James Renegar
    • Categories Convex Optimization Tags ,

    A subgradient method is presented for solving general convex optimization problems, the main requirement being that a strictly-feasible point is known. A feasible sequence of iterates is generated, which converges to within user-specified error of optimality. Feasibility is maintained with a line-search at each iteration, avoiding the need for orthogonal projections onto the feasible region … Read more

    Scalable Robust and Adaptive Inventory Routing

  • Dimitris Bertsimas
  • Swati Gupta
  • Joel Tay
    • Categories Robust Optimization, Transportation Tags , , , , ,

    We consider the finite horizon inventory routing problem with uncertain demand, where a supplier must deliver a particular commodity to its customers periodically, such that even under uncertain demand the customers do not stock out, e.g. supplying residential heating oil to customers. Current techniques that solve this problem with stochastic demand, robust or adaptive optimization … Read more