This course covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) ...

We present an Approximate Dynamic Programming (ADP) approach for the multidimensional knapsack problem (MKP). We approximate the value function (a) using parametric and nonparametric methods and (b) ...

This is an advanced undergraduate course on algorithms. This course examines such topics as greedy algorithms, dynamic programming, graph algorithms, string processing, and algorithms for ...

Recently, the 2025 RAICOM Robotics Developer Competition successfully concluded. Students from Qingdao Agricultural ...

Dynamic programming algorithms are a good place to start understanding what's really going on inside computational biology software. The heart of many well-known programs is a dynamic programming ...

This is a preview. Log in through your library . Abstract This paper proposes a dynamic programming algorithm for decision CPM (DCPM) networks. DCPM is a natural ...

This course studies approximation algorithms – algorithms that are used for solving hard optimization problems. Such algorithms find approximate (slightly suboptimal) solutions to optimization ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

This course is available on the MPA in Data Science for Public Policy, MSc in Applicable Mathematics, MSc in Data Science, MSc in Operations Research & Analytics, MSc in Statistics, MSc in Statistics ...