7 research outputs found

    Linear Generalized Nash Equilibrium Problems

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    In der vorliegenden Arbeit werden verallgemeinerte Nash Spiele (LGNEPs) unter Linearit√§tsannahmen eingef√ľhrt und untersucht. Durch Ausnutzung der speziellen Struktur lassen sich theoretische und algorithmische Resultate erzielen, die weit √ľber die Ergebnisse f√ľr allgemeine LGNEPs hinausgehen

    Leveraged least trimmed absolute deviations

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    The design of regression models that are not affected by outliers is an important task which has been subject of numerous papers within the statistics community for the last decades. Prominent examples of robust regression models are least trimmed squares (LTS), where the k largest squared deviations are ignored, and least trimmed absolute deviations (LTA) which ignores the k largest absolute deviations. The numerical complexity of both models is driven by the number of binary variables and by the value k of ignored deviations. We introduce leveraged least trimmed absolute deviations (LLTA) which exploits that LTA is already immune against y-outliers. Therefore, LLTA has only to be guarded against outlying values in x, so-called leverage points, which can be computed beforehand, in contrast to y-outliers. Thus, while the mixed-integer formulations of LTS and LTA have as many binary variables as data points, LLTA only needs one binary variable per leverage point, resulting in a significant reduction of binary variables. Based on 11 data sets from the literature, we demonstrate that (1) LLTA’s prediction quality improves much faster than LTS and as fast as LTA for increasing values of k and (2) that LLTA solves the benchmark problems about 80 times faster than LTS and about five times faster than LTA, in median

    Crossing Minimal Edge-Constrained Layout Planning using Benders Decomposition

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    We present a new crossing number problem, which we refer to as the edge-constrained weighted two-layer crossing number problem (ECW2CN). The ECW2CN arises in layout planning of hose coupling stations at BASF, where the challenge is to find a crossing minimal assignment of tube-connected units to given positions on two opposing layers. This allows the use of robots in an effort to reduce the probability of operational disruptions and to increase human safety. Physical limitations imply maximal length and maximal curvature conditions on the tubes as well as spatial constraints imposed by the surrounding walls. This is the major difference of ECW2CN to all known variants of the crossing number problem. Such as many variants of the crossing number problem, ECW2CN is NP-hard. Because the optimization model grows fast with respect to the input data, we face out-of-memory errors for the monolithic model. Therefore, we develop two solution methods. In the first method, we tailor Benders decomposition toward the problem. The Benders subproblems are solved analytically and the Benders master problem is strengthened by additional cuts. Furthermore, we combine this Benders decomposition with ideas borrowed from fix-and-relax heuristics to design the Dynamic Fix-and-Relax Pump (DFRP). Based on an initial solution, DFRP improves successively feasible points by solving dynamically sampled smaller problems with Benders decomposition. Because the optimization model is a surrogate model for its time-dependent formulation, we evaluate the obtained solutions for different choices of the objective function via a simulation model. All algorithms are implemented efficiently using advanced features of the GuRoBi-Python API, such as callback functions and lazy constraints. We present a case study for BASF using real data and make the real-world data openly available

    On smoothness properties of optimal value functions at the boundary of their domain under complete convexity

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    This article studies continuity and directional differentiability properties of optimal value functions, in particular at boundary points of their domain. We extend and complement standard continuity results from In particular, we present sufficient conditions for the inner semicontinuity of feasible set mappings and, using techniques from nonsmooth analysis, provide functional descriptions of tangent cones to the domain of the optimal value function. The latter makes the stated directional differentiability results accessible for practical applications

    Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces

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    Tree ensembles can be well-suited for black-box optimization tasks such as algorithm tuning and neural architecture search, as they achieve good predictive performance with little or no manual tuning, naturally handle discrete feature spaces, and are relatively insensitive to outliers in the training data. Two well-known challenges in using tree ensembles for black-box optimization are (i) effectively quantifying model uncertainty for exploration and (ii) optimizing over the piece-wise constant acquisition function. To address both points simultaneously, we propose using the kernel interpretation of tree ensembles as a Gaussian Process prior to obtain model variance estimates, and we develop a compatible optimization formulation for the acquisition function. The latter further allows us to seamlessly integrate known constraints to improve sampling efficiency by considering domain-knowledge in engineering settings and modeling search space symmetries, e.g., hierarchical relationships in neural architecture search. Our framework performs as well as state-of-the-art methods for unconstrained black-box optimization over continuous/discrete features and outperforms competing methods for problems combining mixed-variable feature spaces and known input constraints.Comment: 27 pages, 9 figures, 4 table

    The noncooperative fixed charge transportation problem

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    We introduce the noncooperative fixed charge transportation problem (NFCTP), which is a game-theoretic extension of the fixed charge transportation problem. In the NFCTP, competing players solve coupled fixed charge transportation problems simultaneously. Three versions of the NFCTP are discussed and compared which differ in the treatment of shared social costs. This may be used from central authorities in order to find a socially balanced framework which is illustrated in a numerical study. Using techniques from generalized Nash equilibrium problems with mixed-integer variables we show the existence of Nash equilibria for these models and examine their structural properties. Since there is no unique equilibrium for the NFCTP, we also discuss how to solve the Nash selection problem and, finally, propose numerical methods for the computation of Nash equilibria which are based on mixed-integer programming
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