Results 11 to 20 of about 1,992 (151)
Analysis of Sparse Cutting Planes for Sparse MILPs with Applications to Stochastic MILPs [PDF]
Mathematics of Operations Research, 2018 In this paper, we present an analysis of the strength of sparse cutting planes for mixed integer linear programs (MILP) with sparse formulations. We examine three kinds of problems: packing problems, covering problems, and more general MILPs with the only assumption that the objective function is nonnegative.
Santanu S. Dey +2 more
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Size Constrained Clustering With MILP Formulation [PDF]
IEEE Access, 2020 Clustering is one of the essential tools for data mining since it reveals the natural structures of the unlabeled data. Many clustering algorithms have been proposed in the last decades. However, few of them are designed to adapt prior knowledge that is available in many real applications, such as the sizes of clusters.
Wei Tang 0011 +3 more
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MILP-Based Imitation Learning for HVAC Control [PDF]
IEEE Internet of Things Journal, 2022 To optimize the operation of a HVAC system with advanced techniques such as artificial neural network, previous studies usually need forecast information in their method. However, the forecast information inevitably contains errors all the time, which degrade the performance of the HVAC operation.
Huy Truong Dinh, Daehee Kim 0001
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Fast MILP Models for Division Property
IACR Transactions on Symmetric Cryptology, 2022 Nowadays, MILP is a very popular tool to help cryptographers search for various distinguishers, in particular for integral distinguishers based on the division property. However, cryptographers tend to use MILP in a rather naive way, modeling problems in an exact manner and feeding them to a MILP solver. In this paper, we show that a proper use of some
Patrick Derbez, Baptiste Lambin
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MILP-Based Unsupervised Clustering
IEEE Signal Processing Letters, 2018 In this letter, we discuss the problem of unsupervised clustering of sensor signals based on their information content. In the past, the problem has been formulated as a matrix factorization problem and has been solved with different variants of gradient descent.
Akshay Malhotra, Ioannis D. Schizas
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Parameterized Algorithms for MILPs with Small Treedepth
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 Solving (mixed) integer (linear) programs, (M)I(L)Ps for short, is a fundamental optimisation task with a wide range of applications in artificial intelligence and computer science in general. While hard in general, recent years have brought about vast progress for solving structurally restricted, (non-mixed) ILPs: n-fold, tree-fold, 2-stage stochastic
Cornelius Brand +2 more
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Algorithms and applications for a class of bilevel MILPs
Discrete Applied Mathematics, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Pierre-Louis Poirion +3 more
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MILP models for the Dial-a-ride problem with transfers
EURO Journal on Transportation and Logistics, 2021 Automated vehicles are becoming a reality. Expectations are that AVs will ultimately transform personal mobility from privately owned assets to on-demand services. This transformation will enhance the possibility of sharing trips, leading to shared AVs (SAVs).
Jacopo Pierotti, J. Theresia van Essen
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Iterative MILP methods for vehicle control problems [PDF]
2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601), 2004 Mixed integer linear programming (MILP) is a powerful tool for planning and control problems because of its modeling capability and the availability of good solvers. However, for large models, MILP methods suffer computationally. In this paper, we present iterative MILP algorithms that address this issue. We consider trajectory generation problems with
Matthew G. Earl, Raffaello D'Andrea
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Business Strategy and the Environment, EarlyView.ABSTRACT This study demonstrates how a profitable, lean, and environmentally responsible e‐waste reverse logistics system can be designed using integrated Operations Research (OR) techniques. Addressing the growing urgency of responsible consumption (UN SDG 12) and the projected rise of the e‐waste sector to USD 137.60 billion by 2029, the research ...
Sheeba Pathak, Hajar Fatorachian
wiley +1 more source