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Search · four archives
20 papers · ranked by Valyu relevance
Akif Çördük, Piotr Sielski, Boucher, Alice + 1 more
We introduce a fusion of GPU accelerated primal heuristics for Mixed Integer Programming. Leveraging GPU acceleration enables exploration of larger search regions and faster iterations. A GPU-accelerated PDLP serves as an approximate LP solver, while a new probing cache facilitates rapid roundings and early…
Ruizhi Liu, Liming Xu, Xulin Huang, Jingyan Sui + 4 more
Designing faster algorithms for solving Mixed-Integer Linear Programming (MILP) problems is highly desired across numerous practical domains, as a vast array of complex real-world challenges can be effectively modeled as MILP formulations. Solving these problems typically employs the branch-and-bound algorithm, the…
Kobe Grobben, Phablo F. S. Moura, Hande Yaman
This paper presents an algorithmic study of a class of covering mixed-integer linear programming problems which encompasses classic cover problems, including multidimensional knapsack, facility location and supplier selection problems. We first show some properties of the vertices of the associated polytope, which are…
Kexin Niu, Maxat Kulmanov, Robert Hoehndorf
Current machine learning methods for enzyme function prediction primarily treat proteins as independent entities, ignoring the metabolic context in which they operate. This reductionist approach often generates biologically implausible annotations that fail to satisfy stoichiometric or thermodynamic constraints. While…
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…
Tung Quoc Le, Anh Tuan Nguyen, Viet Anh Nguyen
Lagrangian Relaxation (LR) is a powerful technique for solving large-scale Mixed Integer Linear Programming (MILP), particularly those with decomposable structures, such as vehicle routing or unit commitment problems. By relaxing the coupling constraints, LR enables parallel subproblem solving and often yields tighter…
Patrik Waldmann, Michael DeGiorgio
SCIP (Solving Constraint Integer Programs) is a powerful and versatile optimization solver and framework that can handle mixed integer linear programs, mixed integer quadratic programs, and general mixed integer non-linear programs with a large range of constraints (). While SCIP can be configured in many ways, its…
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…
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…
Alejandro Arenas-Vasco, Juan Carlos Rivera, Maria Gulnara Baldoquín, Yangming Zhou
This paper presents a new formulation and valid constraints for a periodic capacitated vehicle routing problem with multiple depots, heterogeneous fleet, and hard time-windows (MDHFPCVRP-TW). The problem raises from a real-world application in the vending machine industry in Medellín, Colombia. Our main contribution is…
Jinfeng Qiu, Liang Zhao, Xifeng Ning, Dejun Yu + 1 more
Efficient operation of natural gas pipeline networks is essential for minimizing costs and ensuring a stable energy supply. Compressor stations are critical for maintaining pressure throughout the network and represent a substantial portion of both capital investment and operational expenditures. Optimizing compressor…
Wei-Kun Chen, Chang-Long Li, Zhao-Wei Wang, Yu-Hong Dai + 2 more
Presolve for mixed integer programming (MIP) problems aims to eliminate redundant information, strengthen the formulation, and extract useful structural information for the subsequent branch-and-cut process. An important type of such structural information is the variable implications (VIs), which describe how a bound…
Xinyu Gu, Stefan Ivanovic, Daniel W. Feng, Mohammed El-Kebir
Summarizing a collection P of related RNA secondary structures is a key challenge in applications like evolutionary analysis, alternative fold studies and mRNA vaccine design. This requires both clustering the input structures into similar groups and identifying the core structural motifs on which they agree or differ.…
Zhuo Dai, Yefu Zhou, Bibhas Chandra Giri
In supply chain management, the location of facilities, inventory control, and vehicle routing are three key components. This paper incorporates a two-warehouse inventory system into the location- inventory-routing problems (LIRPs) and develops LIRP models with two warehouses in one-level, two-level, and three-level…
Luigi Catacuzzeno, Maurizio G. Cavaliere, Antonio Michelucci
Pump-Leak (P-L) models are powerful tools in membrane and cellular physiology, providing a quantitative framework to understand how cells regulate intracellular ion concentrations, cell volume, and membrane potential thorugh ion transport mechanisms. However, constructing a P-L model for a specific cell type is…
Ke Chen, Abhishek Talesara, Sanchal Thakkar, Mingfu Shao
The minimum flow decomposition problem abstracts a set of key tasks in bioinformatics, including metagenome and transcriptome assembly. These tasks, collectively known as multi-assembly, aim to reconstruct multiple genomic sequences from reads obtained from mixed samples. The reads are first organized into a directed…
Frans Zdyb, Julius B. Kirkegaard
Biological image and video analysis is full of discrete decisions: whether an object is present, which multi-hypothesis detections are real, whether two detections are tracking the same object, or whether a cell divides or not. Standard pipelines resolve these locally and in sequence, e.g through non-max suppression…
Parth Brahmbhatt, David L. Cole, Victor M. Zavala, Styliani Avraamidou
Using Graph Modeling and Multi-Parametric Programming Authors: Parth Brahmbhatt, David L. Cole, Victor M. Zavala, Styliani Avraamidou Benders decomposition is a widely used method for solving large and structured optimization problems, but its performance is affected by the repeated solution of subproblems. We propose…
A.J.R. Cotter
A simulator, ‘ECOLPS’ in R, is developed and trialed for ecological studies of closed aquatic ecosystems. Its constraint-based approach contrasts with function-based models widely applied in ecology. Total gross production (ΣGP) by ‘wild components’ (= species/life stages, grouped by ecological roles) is maximized…
Authors not listed
Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…