Abstract: Energy optimization is a critical challenge in wireless sensor networks (WSNs) due to its direct impact on the network lifetime. This paper proposes the use of the K-means algorithm combined ...

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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Aim to minimize the combined fixed and transportation costs by deciding which of five plants to keep open or what have to close.

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 ...

Global consumer media usage, including all digital and traditional media channels, increased 2.4% in 2024 to an average of 57.2 hours per week, following a sharp deceleration in time spent with media ...

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 ...