Algorithms are turning up in the most unlikely places, promising to assert mathematical probability into corners of our lives where intuition, instinct and hunches have long held sway.

Dynamic Programming Algorithms in Computational Biology Publication Trend The graph below shows the total number of publications each year in Dynamic Programming Algorithms in Computational Biology.

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

Ever wondered how computers multiply huge numbers with hundreds or even thousands of digits? The process may seem simple, but ...

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 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 ...

It 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) .

This paper presents the results of experimentation on the development of an efficient branch-and-bound algorithm for the solution of zero-one linear mixed integer programming problems. An implicit ...

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, ...