Operations Research Proceedings 2014: Selected Papers of the by Marco Lübbecke, Arie M.C.A. Koster, Peter Letmathe, Reinhard

By Marco Lübbecke, Arie M.C.A. Koster, Peter Letmathe, Reinhard Madlener, Britta Peis, Grit Walther

This e-book encompasses a collection of refereed papers offered on the "International convention on Operations study (OR 2014)", which came about at RWTH Aachen collage, Germany, September 2-5, 2014. greater than 800 scientists and scholars from forty seven international locations attended OR 2014 and awarded greater than 500 papers in parallel topical streams, in addition to detailed award periods. The subject matter of the convention and its complaints is "Business Analytics and Optimization".

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Extra info for Operations Research Proceedings 2014: Selected Papers of the Annual International Conference of the German Operations Research Society (GOR), RWTH Aachen University, Germany, September 2-5, 2014

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I, j∈[d] i< j In this short paper we summarize our new results on the structure of the optimal layouts, present the ILP and SDP models that follow from those results and provide representative computational results. Formal proofs and detailed computational results are omitted due to space limitations and are provided in the full paper [3]. 2 The Structure of Optimal Layouts The definition of the (DREFLP) suggests that the spaces between the departments can be of arbitrary lengths in a feasible layout.

The Lagrangian equation L includes coordinators λ for load balance (LB) and μ for reserve balance (RB) [1]: min L = max{ min Cpower + λ(LB) + μ(RB) } λ,μ p,s,w,x (6) The dual problem of L can be decomposed into subpoblems for thermal and hydraulic units which can be solved by Dynamic Programming and Network Flow Optimization, respectively. The aim of maximizing the dual problem is achieved iteratively by adjusting λ and μ using gradient descent method. Finally, in the third stage the power and natural gas system is optimized by LP again by adopting the dispatch decisions found in the second stage and with linearized heat consumption curves.

Realistic evaluation of logistic regression using coarse classed data. 2 Methodology Imbalance Correction: A standard approach for class imbalance correction consists in sampling [9]: In undersampling a random subset of the majority class is used for training, whereas oversampling randomly duplicates instances of the minority class. Some classifiers allow weighting of observations during training, which is a straightforward, alternative intrinsic imbalance correction to sampling, if one downweights majority and upweights minority class observations.

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