Abstract: We consider the problem of maximizing the reliability of a series-parallel system given cost and weight constraints on the system. The number of components in each subsystem, and the choice ...

In this study, we developed a mathematical model to maximize economic returns in small-scale agricultural production units. The study was conducted on a rural property in Medianeira, Paraná, Brazil, ...

Influence Maximization (IM) is a fundamental problem in network science with applications in viral marketing, information dissemination, cybersecurity, and epidemiology. Classical IM solvers often ...

In the evolving landscape of decision intelligence, few mathematical breakthroughs have had as profound an impact as linear programming. At the heart of this revolutionary approach stands a brilliant ...

In today's data-driven world, decision-making is more complex than ever. Organizations across various industries face the challenge of optimizing resources, costs, and operations while meeting ...

ABSTRACT: This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two ...

Operations research professionals need the best linear programming software for Windows to solve optimization problems. Below we offer a tool that comes with all the essentials to help you perform a ...

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 ...

Abstract: This article proposes a second-order conic programming (SOCP) approach to solve distributionally robust two-stage linear programs over 1-Wasserstein balls. We start from the case with ...

Although plant proteins are often considered to have less nutritional quality because of their suboptimal amino acid (AA) content, the wide variety of their sources, both conventional and emerging, ...