Abstract: The algorithms and software tools for solving large-scale NP-hard MILP (mixed-integer linear programming) problems are analyzed, specifically focusing on the modeling of electric power ...

ABSTRACT: This article examines some of the properties of quasi-Fejer sequences when used in quasi-gradiental techniques as an alternative to stochastic search techniques for optimizing unconstrained ...

This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as a mixed integer ...

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This project uses ordinal optimization for computationally efficient sizing of a hybrid energy system containing PV panels, batteries, diesel generators, and an intermittent grid. It also utilizes ...

An Introduction to Programming and Computer Science with Python, second edition is a free, open source textbook available under a CC BY-NC-SA license. Originally developed for UVM’s CS 1210 ...

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...

Mixed Integer Linear Programming (MILP) is essential for modeling complex decision-making problems but faces challenges in computational tractability and requires expert formulation. Current deep ...

ABSTRACT: This study proposes a novel approach to optimizing individual work schedules for book digitization using mixed-integer programming (MIP). By leveraging the power of MIP solvers, we aimed to ...