Successive Linear Programming (SLP) algorithms solve nonlinear optimization problems via a sequence of linear programs. They have been widely used, particularly in the oil and chemical industries, ...

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 ...

Introduction to theory of algorithms guided by basic Python programming. Algorithmic thinking: Do you know how to multiply integers? Basic toolkit for the design and analysis of algorithms, and an ...

Dynamic programming (DP) algorithms have become indispensable in computational biology, addressing problems that range from sequence alignment and phylogenetic inference to RNA secondary structure ...

Probabilistic Programming and Inference Algorithms Publication Trend The graph below shows the total number of publications each year in Probabilistic Programming and Inference Algorithms.

MA314 Half Unit Algorithms and Programming This information is for the 2017/18 session. Teacher responsible ...

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 ...

This course continues our data structures and algorithms specialization by focussing on the use of linear and integer programming formulations for solving algorithmic problems that seek optimal ...

Computers can be used to help solve problems. However, before a problem can be tackled, it must first be understood. Computational thinking helps us to solve problems. Designing, creating and refining ...