17 papers · ranked by Valyu relevance
Radoslaw Ryńca, Yasmin Ziaeian, Claudia Noemi González Brambila
In the past few decades, any type of organization, from factories to government organizations, the banking sector, or educational institutions concentrates on increasing profit margins. To achieve this, one of the key factors is to achieve maximum output with minimum resources (input). Therefore, having an optimal plan…
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…
Hao Cheng, Keyu Xu, Jinghui Li, Kuruvilla Joseph Abraham
Low-cost genome-wide single-nucleotide polymorphisms (SNPs) are routinely used in animal breeding programs. Compared to SNP arrays, the use of whole-genome sequence data generated by the next-generation sequencing technologies (NGS) has great potential in livestock populations. However, sequencing a large number of…
Samir Ismail, Amith Umesh, Mohid Khan, Ahmed Moutwakil + 11 more
Background/Objectives: Ready-to-use therapeutic foods (RUTFs) are a common treatment for children under five years diagnosed with acute malnutrition. However, traditional RUTFs are often not locally produced, and the costs of the RUTF can be a barrier to access in India and Pakistan. Our goal was to utilize linear…
Ahmad Abdi, Gérard Cornuéjols, Bertrand Guenin, Levent Tunçel
A rational number is dyadic if it has a finite binary representation $p/2^k$, where p is an integer and k is a nonnegative integer. Dyadic rationals are important for numerical computations because they have an exact representation in floating-point arithmetic on a computer. A vector is dyadic if all its entries are…
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 $x_{1},…,x_{n}$…
Mohamed O. Hegazi
This paper presents a novel approach for simulating and optimizing production costing systems using linear programming. The proposed method employs a linear programming algorithm to simulate the behavior of production costs and to derive optimal solutions, including cost minimization, resource maximization, and…
María J. Nueda, Carmen Gandía, Mariola D. Molina, Eugene Demidenko
The search of separation hyperplanes is an efficient way to find rules with classification purposes. This paper presents an alternative mathematical programming formulation to existing methods to find a discriminant hyperplane. The hyperplane H is found by minimizing the sum of all the distances to the area assigned to…
Dariusz Lesniowski, Nicolas Terliesner
Background Access to pediatric medical care is a critical factor in determining health outcomes. Hospital landscape restructuring processes need to consider the geographical accessibility of pediatric emergency and inpatient services. Public regulators in Germany aim for a travel time to the closest pediatric emergency…
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…
Jan Schröder, Yair Censor, Philipp Süss, Karl-Heinz Küfer
Given a family of linear constraints and a linear objective function one can consider whether to apply a Linear Programming (LP) algorithm or use a Linear Superiorization (LinSup) algorithm on this data. In the LP methodology one aims at finding a point that fulfills the constraints and has the minimal value of the…
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…
Ibrahim M. Hezam, Sarah A. H. Taher, Abdelaziz Foul, Adel Fahad Alrasheedi
'Adel Fahad Alrasheedi'] We develop neutrosophic goal programming models for sustainable resource planning in a healthcare organization. The neutrosophic approach can help examine the imprecise aspiration levels of resources. For deneutrosophication, the neutrosophic value is transformed into three intervals based on…
Stefania Bellavia, Jacek Gondzio, Margherita Porcelli
A new relaxed variant of interior point method for low-rank semidefinite programming problems is proposed in this paper. The method is a step outside of the usual interior point framework. In anticipation to converging to a low-rank primal solution, a special nearly low-rank form of all primal iterates is imposed. To…
S. Angammal, G. Hannah Grace
In agriculture, crop planning and land distribution have been important research subjects. The distribution of land involves several multi-functional tasks, such as maximizing output and profit and minimizing costs. These functions are influenced by a variety of uncertain elements, including yield, crop price, 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…
Berhanu Belay, Adane Abebaw, Omar A. Alzubi
This manuscript presents a technique for solving a multiple-objective probabilistic fractional programming problem with discrete random variables. A multiple-objective probabilistic mathematical model is constructed with fractional objectives. In the model, some parameters of coefficients and right hand side parameters…