In particular, RNA folding – a classic application of dynamic programming – utilises recurrence relations to predict the most stable secondary structures based on base-pair interactions.

A technique for finding MINSUM and MINMAX solutions to multi-criteria decision problems, called Multi Objective Dynamic Programming, capable of handling a wide range of linear, nonlinear, ...

Dynamic programming algorithms are developed for optimal capital allocation subject to budget constraints. We extend the work of Weingartner [17] and Weingartner and Ness [19] by including multilevel ...

Dynamic Programming and Optimal Control is offered within DMAVT and attracts in excess of 300 students per year from a wide variety of disciplines. It is an integral part of the Robotics, System and ...

IEMS 469: Dynamic Programming VIEW ALL COURSE TIMES AND SESSIONS Prerequisites Basic knowledge of probability (random variables, expectation, conditional probability), optimization (gradient), ...

Description: Focuses on the application of the tools of dynamic optimization to problems in economics. Covers continuous-time and discrete-time dynamic optimization techniques, including the calculus ...

CSCA 5414: Dynamic Programming, Greedy Algorithms CSCA 5414: Dynamic Programming, Greedy Algorithms Get a head start on program admission Preview this course in the non-credit experience today! Start ...

When enabled by flexible AI programming languages, quantum computing performs AI calculations much faster, and at a greater scale.

Dan Zhang and Larry Weatherford. 2017. Dynamic Pricing for Network Revenue Management: A New Approach and Application in the Hotel Industry. INFORMS Journal on Computing, 29 (1): 18-35. Dynamic ...