Search · four archives
Search · four archives
26 papers · ranked by Valyu relevance
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…
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…
Weili Zhang, Charles Nicholson
The objective scaling ensemble approach is a novel two-phase heuristic for integer linear programming problems shown to be effective on a wide variety of integer linear programming problems. The technique identifies and aggregates multiple partial solutions to modify the problem formulation and significantly reduce the…
Albert No
The size of the largest binary single deletion code has been unknown for more than 50 years. It is known that Varshamov-Tenengolts (VT) code is an optimum single deletion code for block length $n\leq10$; however, only a few upper bounds of the size of single deletion code are proposed for larger n. We provide improved…
Martin Gonzalez, Jose J. López-Espín, Juan Aparicio, El-Ghazali Talbi + 1 more
'El-Ghazali Talbi' 'Nicholas Higham'] Mixed Integer Linear Programs (MILPs) are usually NP-hard mathematical programming problems, which present difficulties to obtain optimal solutions in a reasonable time for large scale models. Nowadays, metaheuristics are one of the potential tools for solving this type of problems…
Authors not listed
Automated chemistry platforms hold the potential to enable large-scale organic synthesis campaigns, such as producing a library of compounds for biological evaluation. The efficiency of such platforms will depend on the schedule according to which the synthesis operations are executed. In this work, we study the…
Behrooz Bodaghi, Nadezda Sukhorukova
In this paper we propose a new efficient linear programming based approach for multi-resource allocation and location problems in disaster management. Such problems require an integer solution and therefore, in most cases, the computations rely on integer and mixed-integer linear programming solvers. In general, these…
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…
Henri Schmidt, Benjamin J. Raphael
Reconstructing unobserved ancestral states of a phylogenetic tree provides insight into the history of evolving systems and is one of the fundamental problems in phylogenetics. For a fixed phylogenetic tree, the most parsimonious ancestral reconstruction – a solution to the small parsimony problem – can be efficiently…
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…
Gioni Mexi, Sébastien Designolle, Mathieu Besançon
We propose a primal heuristic for quadratic mixed-integer problems. Our method extends the Boscia framework – originally a mixedinteger convex solver leveraging a Frank-Wolfe-based branch-and-bound approach – to address nonconvex quadratic objective functions and constraints. We reformulate nonlinear constraints…
Authors not listed
Experimental design plays an important role in efficiently acquiring informative data for system characterization and deriving robust conclusions under resource limitations. Recent advancements in high-throughput experimentation coupled with machine learning have notably improved experimental procedures. While Bayesian…
David A. Liñán, Luis A. Ricardez-Sandoval
Mixed integer nonlinear programming (MINLP) in chemical engineering originated as a tool for solving optimal process synthesis and design problems. Since then, the application of MINLP has expanded to encompass control and operational decisions that are in line with the arising challenges faced by the industry, e.g.…
Sleiman Mhanna, Isam Saedi, Pierluigi Mancarella
—In light of the increasing coupling between electricity and gas networks, this paper introduces two novel iterative methods for efficiently solving the multiperiod optimal electricity and gas flow (MOEGF) problem. The first is an iterative MILPbased method and the second is an iterative LP-based method with an…
Jakob Witzig, Timo Berthold, Stefan Heinz
Mixed integer nonlinear programs (MINLPs) are arguably among the hardest optimization problems, with a wide range of applications. MINLP solvers that are based on linear relaxations and spatial branching work similar as mixed integer programming (MIP) solvers in the sense that they are based on a branch-and-cut…
Zixiang Xu
Gene knockout has been used to improve the conversion ratio of strains for some chemical products. Based on mixed integer bi-level linear programming (MIBLP) and cell network models, there have been several algorithms to predict the target for deletion to improve the productivity of chemicals. At present, the cell…
Mercè Llabrés, Gabriel Valiente
Beside socio-economic issues, coronavirus pandemic COVID-19, the infectious disease caused by the newly discovered coronavirus SARS-CoV-2, has caused a deep impact in the scientific community, that has considerably increased its effort to discover the infection strategies of the new virus. Among the extensive and…
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…
Mengzhen Guo, Stefan Grünewald
We present Lpnet, a variant of the widely used Neighbor-net method that approximates pairwise distances between taxa by a circular phylogenetic network. We first apply standard methods to construct a binary phylogenetic tree and then use integer linear programming to compute an optimal circular orderings that agrees…
Richard Schuster, Jeffrey O. Hanson, Matt Strimas-Mackey, Joseph R. Bennett
The resources available for conserving biodiversity are limited, and so protected areas need to be established in places that will achieve objectives for minimal cost. Two of the main algorithms for solving systematic conservation planning problems are Simulated Annealing (SA) and Integer linear programming (ILP).…
Olesya Melnichenko, Venkat S. Malladi
In the field of genomics, bioinformatics pipelines play a crucial role in processing and analyzing vast biological datasets. These pipelines, consisting of interconnected tasks, can be optimized for efficiency and scalability by leveraging cloud platforms such as Microsoft Azure. The choice of compute resources…
Sergio Garcia, Cong T. Trinh
Living cells optimize their fitness against constantly changing environments to survive. Goal attainment optimization is a mathematical framework to describe the simultaneous optimization of multiple conflicting objectives that must all reach a performance above a threshold or goal. In this study, we applied goal…
Authors not listed
We present a vector-based method to balance chemical reactions. The algorithm builds candidates in a deterministic way, removes duplicates, and always prints coefficients in the lowest whole-number form. For redox cases, electrons and protons/hydroxide are treated explicitly, so both mass and charge are balanced. We…
Authors not listed
Solving optimization problems, especially for nonlinear and constrained systems, is a challenge. Decades of specialized algorithms have been developed for general and special cases of root finding, minimization (including constraints), for parameter estimation, and mapping connected spaces. These approaches typically…
Liwei Cao, Danilo Russo, Vassilios S. Vassiliadis, Alexei Lapkin
A mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed to identify physical models from noisy experimental data. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the number of predictor…
Tobias Seidel, Lena-Marie Ränger, Thomas Grützner, Michael Bortz
In this work we present a new approach that we use to simulate and optimize multiple dividing wall columns at the same time. Instead of considering all model equations as constraints and all process variables as optimization variables in a large and highly nonlinear optimization problem we only incorporate a subset of…