† Department of Chemical Engineering, Graduate School of Engineering, Tohoku University, 6-6-07 Aramaki Aza Aoba, Aoba-ku, Sendai, Miyagi 980-8579, Japan ‡ Department of Environmental Study for ...

Abstract: Many methods are known to solve the problem of real-valued and static quadratic programming (QP) effectively. However, few of them are still useful to solve the time-varying QP problem in ...

Abstract: Orthogonal frequency-division multiplexing (OFDM)-based joint radar communication (JRC) systems have signal distortion when the transmit signal has a high peak-to-average power ratio (PAPR).

Solving Ordinary Differential Equations (ODEs) is an essential and very challenging computational problem in many areas of science and engineering like physics, biology, control system, and economics.

The rising demand for electricity presents significant challenges to grid stability. Demand response programs address this issue by incentivizing consumers to adjust consumption during peak periods.

This paper proposes a family of line-search methods to deal with weighted orthogonal procrustes problems. In particular, the proposed family uses a search direction based on a convex combination ...

Recent advancements in quantum computing and quantum-inspired algorithms have sparked renewed interest in binary optimization. These hardware and software innovations promise to revolutionize solution ...

Quantum annealing emerges as a promising approach for tackling complex scheduling problems such as the resource-constrained project scheduling problem (RCPSP). This study represents the first ...

Linear Programming has been used to solve optimization problems in banking, forestry, petroleum, and medical industries. Optimization can be completed with linear and non linear models. There are ...

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 ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...