Dynamic programming is a methodological framework for solving optimisation problems that evolve over time by breaking them into simpler subproblems. Central to this approach is the principle of ...

Adaptive optimal control in dynamic systems merges the principles of adaptation and optimality to regulate systems whose behaviour or environment evolve over time. At its core, this field addresses ...

The k-Means clustering problem on n points is NP-Hard for any dimension d ≥ 2, however, for the 1D case there exists exact polynomial time algorithms. The best ...

Walmart can now update prices instantly at many stores, meaning deals (and regular prices) may change faster than shoppers are used to. While Walmart says it’s not using surge pricing, the tech allows ...

This research communication aims to present a curricular proposal to relate the importance of the application of optimal control theory for dynamic supply chains for industrial engineering students ...

Lawmakers in Harrisburg are looking at bills to tackle dynamic pricing. Consumers see dynamic prices on purchases like airfare, hotel rooms and concert tickets. It means when there's high demand and ...

Abstract: This paper proposes an adaptive dynamic programming (ADP) algorithm based on a dynamic event-triggered mechanism (ETM) for the optimal control problem of a class of continuous-time nonlinear ...

Welcome to Play Smart, a regular GOLF.com game-improvement column that will help you become a smarter, better golfer. To generate your maximum power, you’ve got to know how to properly shift your ...

To address grid variability caused by renewable energy integration and to maintain grid reliability and resilience, hydropower must quickly adjust its power generation over short time periods. This ...

This study develops a unified framework for optimal portfolio selection in jump–uncertain stochastic markets, contributing both theoretical foundations and computational insights. We establish the ...