HBR revives “maximizing shareholder value”—what Jack Welch called "the dumbest idea in the world"—treating customers as ...
Abstract: Optimization under multiple linear constraints is important for practical systems with individual power constraints, per-antenna power constraints, and/or interference constraints as in ...
† 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 ...
Positional accuracy of cartographic products is typically evaluated using positional discrepancies and point-based techniques. However, using linear features has some advantages over the point-based ...
Phase-only beamforming offers a hardware-efficient alternative to amplitude tapering, but achieving low sidelobe levels while maintaining high array efficiency remains challenging. This paper proposes ...
This toolbox brings robotics-specific functionality to Python, and leverages Python's advantages of portability, ubiquity and support, and the capability of the open-source ecosystem for linear ...
Influence Maximization (IM) is a fundamental problem in network science with applications in viral marketing, information dissemination, cybersecurity, and epidemiology. Classical IM solvers often ...
Abstract: This paper addresses the robust adaptive beamforming (RAB) problem via the worst-case signal-to-interference-plus-noise ratio (SINR) maximization over distributional uncertainty sets for the ...
The examples are nothing if not relatable: preparing breakfast, or playing a game of chess or tic-tac-toe. Yet the idea of learning from the environment and taking steps that progress toward a goal ...
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 ...
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 ...
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