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, ...

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

Jonathan Eckstein, Nonlinear Proximal Point Algorithms Using Bregman Functions, with Applications to Convex Programming, Mathematics of Operations Research, Vol. 18, No. 1 (Feb., 1993), pp. 202-226 ...

MG4C6.2 Mathematical Programming: Introduction to theory and the solution of linear and nonlinear programming problems: basic solutions and the simplex method, convex programming and KKT conditions, ...

Formulate linear and integer programming problems for solving commonly encountered optimization problems. Understand how approximation algorithms compute solutions that are guaranteed to be within ...

Course Description This course is part three of a specialization on algorithms and data structures. It covers basic algorithm design techniques such as divide and conquer, dynamic programming, and ...

Advanced study in models of computation, programming languages and algorithms with a specific focus on concurrent programming. The course includes models of computation, programming language paradigms ...

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

GCSE Computer Science Computational thinking, algorithms and programming learning resources for adults, children, parents and teachers.