Search · four archives
Search · four archives
16 papers · ranked by Valyu relevance
Mikhail A. Bragin
Mixed-Integer Linear Programming (MILP) plays an important role across a range of scientific disciplines and within areas of strategic importance to society. The MILP problems, however, suffer from combinatorial complexity. Because of integer decision variables, as the problem size increases, the number of possible…
Jiayi Zhang, Chang Liu, Junchi Yan, Xijun Li + 2 more
'Mingxuan Yuan'] This paper surveys the trend of leveraging machine learning to solve mixed integer programming (MIP) problems. Theoretically, MIP is an NPhard problem, and most of the combinatorial optimization (CO) problems can be formulated as the MIP. Like other CO problems, the human-designed heuristic algorithms…
Mikhail A. Bragin, Emily L. Tucker
Mixed-Integer Linear Programming (MILP) plays an important role across a range of scientific disciplines and within areas of strategic importance to society. The MILP problems, however, suffer from combinatorial complexity. Because of integer decision variables, as the problem size increases, the number of possible…
Lara Scavuzzo, Karen Aardal, Andrea Lodi, Neil Yorke-Smith
Mixed Integer Linear Programming (MILP) is a pillar of mathematical optimization that offers a powerful modeling language for a wide range of applications. The main engine for solving MILPs is the branch-and-bound algorithm. Adding to the enormous algorithmic progress in MILP solving of the past decades, in more recent…
Jian Liu, Rui Bo, Siyuan Wang
Enhancing existing transmission lines is a useful tool to combat transmission congestion and guarantee transmission security with increasing demand and boosting the renewable energy source. This study concerns the selection of lines whose capacity should be expanded and by how much from the perspective of independent…
Shuli Zeng, Mengjie Zhou, Sijia Zhang, Yixiang Hu + 2 more
'Xiang-Yang Li'] Constraint ordering plays a critical role in the efficiency of Mixed-Integer Linear Programming (MILP) solvers, particularly for large-scale problems where poorly ordered constraints trigger increased LP iterations and suboptimal search trajectories. This paper introduces CLCR (Contrastive…
Luke Fina, Christopher Petersen, Matthew Hale
Feasibility Guarantees Authors: ['Luke Fina' 'Christopher Petersen' 'Matthew Hale'] In this paper we solve mixed-integer linear programs (MILPs) via distributed asynchronous saddle point computation. To solve a MILP, we relax it with a linear program approximation. We first show that if the linear program relaxation…
Konstantinos Gkiotsalitis, Tao Liu
Considering the COVID-19 Capacity Limits: A Dutch Case Study Authors: Konstantinos Gkiotsalitis, Tao Liu The COVID-19 pandemic has had serious adverse impacts on public transport service providers. Most public transport lines exhibit reduced ridership levels while, at the same time, some of them may exhibit passenger…
Zayn Wang
Mixed-Integer Programming (MIP), particularly Mixed-Integer Linear Programming (MILP) and Mixed-Integer Quadratic Programming (MIQP), has found extensive applications in domains such as portfolio optimization and network flow control, which inclusion of integer variables or cardinality constraints renders these…
Noah Schulhof, Pattara Sukprasert, Eytan Ruppin, Samir Khuller + 1 more
'Alejandro A. Schäffer'] Integer linear programs (ILPs) and mixed integer programs (MIPs) often have multiple distinct optimal solutions, yet the widely used Gurobi optimization solver returns certain solutions at disproportionately high frequencies. This behavior is disadvantageous, as, in fields such as biomedicine…
Xuan Lin
This paper presents a comparative study of data-driven acceleration techniques for mixed-integer bilinear programs (MIBLPs) applied to robot motion planning. MIBLPs combine discrete decision variables and nonlinear constraints, making them computationally challenging for real-time robotics applications. We investigate…
Pacheco, Bruno Machado, Antunes, Pedro Marcolin + 10 more
This paper introduces a novel algorithm for Mixed-Integer Nonlinear Programming (MINLP) problems with multilinear interpolations of look-up tables. These problems arise when objectives or constraints contain black-box functions only known at a finite set of evaluations on a predefined grid. We derive a piecewise-linear…
K. H. Benjamin Leung, Nasrin Yousefi, Timothy C. Y. Chan, Ahmed M. Bayoumi
Putting the 4 components together, a general optimization model can be formulated as follows: maximize f ( x 1 , … , x n ; α 1 , … , α k ) subject to g i ( x 1 , … , x n ; α 1 , … , α k ) ≥ 0 , i = 1 , … , m This optimization model aims to maximize an objective function $f$ with $n$ decision variables $x_{1},…,x_{n}$…
Yongzheng Dai, Chen Chen
We develop a novel primal heuristic for nonconvex Mixed-Integer Quadratically Constrained Quadratic Programs (MIQCQPs). The method is built around a convex approximation that is dynamically adjusted within a feasibility-pump-style alternating heuristic. Approximations are adjusted based on the structure of the MIQCQP…
Daniel Molina-Pérez, Edgar Alfredo Portilla-Flores, Efrén Mezura-Montes, Eduardo Vega-Alvarado + 2 more
'Efrén Mezura-Montes' 'Eduardo Vega-Alvarado' 'María Bárbara Calva-Yañez' 'Thomas Stützle'] Mixed integer nonlinear programming (MINLP) addresses optimization problems that involve continuous and discrete/integer decision variables, as well as nonlinear functions. These problems often exhibit multiple discontinuous…
Elisabeth Gaar, Jon Lee, Ivana Ljubić, Markus Sinnl + 1 more
We study a class of integer bilevel programs with second-order cone constraints at the upper-level and a convex-quadratic objective function and linear constraints at the lower-level. We develop disjunctive cuts (DCs) to separate bilevel-infeasible solutions using a second-order-cone-based cut-generating procedure. We…