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In this work, we develop an adaptive, multivariate partitioning algorithm for solving mixed-integer nonlinear programs (MINLP) with multi-linear terms to global optimality. This iterative algorithm primarily exploits the advantages of…

Optimization and Control · Mathematics 2019-02-05 Harsha Nagarajan , Mowen Lu , Site Wang , Russell Bent , Kaarthik Sundar

Semidefinite Programming (SDP) provides tight lower bounds for Optimal Power Flow problems. However, solving large-scale SDP problems requires exploiting sparsity. In this paper, we experiment several clique decomposition algorithms that…

Optimization and Control · Mathematics 2019-12-20 Julie Sliwak , Miguel Anjos , Lucas Létocart , Jean Maeght , Emiliano Traversi

The submodular function maximization is an attractive optimization model that appears in many real applications. Although a variety of greedy algorithms quickly find good feasible solutions for many instances while guaranteeing…

Data Structures and Algorithms · Computer Science 2018-11-13 Naoya Uematsu , Shunji Umetani , Yoshinobu Kawahara

Integer linear programming (ILP) encompasses a very important class of optimization problems that are of great interest to both academia and industry. Several algorithms are available that attempt to explore the solution space of this class…

Emerging Technologies · Computer Science 2018-08-31 Fabio L. Traversa , Massimiliano Di Ventra

Integer Linear Programming (ILP) serves as a versatile framework for modeling a wide range of combinatorial optimization problems, typically addressed by sophisticated exact solvers or heuristics. While learning-based approaches have…

Machine Learning · Computer Science 2026-05-29 Kyuil Sim , Sanghyeok Choi , Jinkyoo Park

We consider the uncapacitated three-level lot-sizing and replenishment problem with a distribution structure. In this NP-hard problem, a single production plant sends the produced items to replenish warehouses from where they are dispatched…

Optimization and Control · Mathematics 2021-04-20 Jesus O. Cunha , Rafael A. Melo

MAP inference for general energy functions remains a challenging problem. While most efforts are channeled towards improving the linear programming (LP) based relaxation, this work is motivated by the quadratic programming (QP) relaxation.…

Machine Learning · Computer Science 2012-06-22 Patrick Pletscher , Sharon Wulff

Our interest in this paper is in optimisation problems that are intractable to solve by direct numerical optimisation, but nevertheless have significant amounts of relevant domain-specific knowledge. The category of heuristic search…

Artificial Intelligence · Computer Science 2016-11-14 Ashwin Srinivasan , Gautam Shroff , Lovekesh Vig , Sarmimala Saikia , Puneet Agarwal

This paper considers a bilevel program, which has many applications in practice. To develop effective numerical algorithms, it is generally necessary to transform the bilevel program into a single-level optimization problem. The most…

Optimization and Control · Mathematics 2023-02-15 Yuwei Li , Gui-Hua Lin , Jin Zhang , Xide Zhu

This letter concerns optimal power transmission line inspection formulated as a proposed generalization of the traveling salesman problem for a multi-route one-depot scenario. The problem is formulated for an inspection vehicle with a…

Robotics · Computer Science 2023-02-03 František Nekovář , Jan Faigl , Martin Saska

We propose a new pricing strategy for column generation (CG), referred to as Template pricing. This method is motivated by the desire to coordinate solutions of different pricing subproblems in order to accelerate the convergence of the CG…

Optimization and Control · Mathematics 2026-04-15 Luke Marshall , Prachi Shah , Santanu S. Dey

The load pick-up (LPP) problem searches the optimal configuration of the electrical distribution system (EDS), aiming to minimize the power loss or provide maximum power to the load ends. The piecewise linearization (PWL) approximation…

Optimization and Control · Mathematics 2018-11-27 Jingyang Yun , Yun Zhou , Weidong Hu , Peichao Zhang , Zheng Yan , Donghan Feng

We present a technique for producing valid dual bounds for nonconvex quadratic optimization problems. The approach leverages an elegant piecewise linear approximation for univariate quadratic functions due to Yarotsky, formulating this…

Optimization and Control · Mathematics 2021-03-30 Ben Beach , Robert Hildebrand , Joey Huchette

We propose a novel global solution algorithm for the network-constrained unit commitment problem incorporating a nonlinear alternating current model of the transmission network, which is a nonconvex mixed-integer nonlinear programming…

Optimization and Control · Mathematics 2018-11-27 Jianfeng Liu , Anya Castillo , Jean-Paul Watson , Carl D. Laird

Given a weighted graph $G$, a minimum weight $\alpha$-spanner is a least-weight subgraph $H\subseteq G$ that preserves minimum distances between all node pairs up to a factor of $\alpha$. There are many results on heuristics and…

Data Structures and Algorithms · Computer Science 2024-06-28 Fritz Bökler , Markus Chimani , Henning Jasper , Mirko H. Wagner

An optimization problem considering AC power flow constraints and integer decision variables can usually be posed as a mixed-integer quadratically constrained quadratic program (MIQCQP) problem. In this paper, first, a set of valid linear…

Optimization and Control · Mathematics 2015-09-18 Qifeng Li

Mixed integer linear programming (MILP) solvers expose hundreds of parameters that have an outsized impact on performance but are difficult to configure for all but expert users. Existing machine learning (ML) approaches require training on…

Machine Learning · Computer Science 2025-09-25 Connor Lawless , Yingxi Li , Anders Wikum , Madeleine Udell , Ellen Vitercik

This study introduces a mixed-integer linear programming (MILP) model, effectively co-optimizing patrolling, damage assessment, fault isolation, repair, and load re-energization processes. The model is designed to solve a vital operational…

Systems and Control · Electrical Eng. & Systems 2024-01-12 Ali Jalilian , Babak Taheri , Daniel K. Molzahn

We apply column generation to approximating complex structured objects via a set of primitive structured objects under either the cross entropy or L2 loss. We use L1 regularization to encourage the use of few structured primitive objects.…

Machine Learning · Computer Science 2016-02-16 Julian Yarkony , Kamalika Chaudhuri

Dynamic economic dispatch (DED) problem considering prohibited operating zones (POZ), ramp rate constraints, transmission losses and spinning reserve constraints is a complicated non-linear problem which is difficult to solve efficiently.…

Optimization and Control · Mathematics 2017-04-07 Shanshan Pan , Jinbao Jian , Linfeng Yang