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A Tutorial on Integer - A good source to learn Integer Optimization solution algorithms and their applications.
 
Archives of ORNET@JISCMAIL.AC.UK - Archives of ORNET@JISCMAIL.AC.UK
 
Artificial Free Solution Algorithms - Contains notes and numerical examples for three distinct solution algorithms for general linear programs without using artificial variables, constraint, or auxiliary objective function.
 
Computer-assisted Learning - Computer assisted learning is a collection of experimentation and simulation using computer software packages, such as WinQSB, to understand the concepts and techniques of OR/MS.
 
Constraints FAQ - From AI-related FAQs, frequently asked questions regarding constraint programming.
 
Dictionary of Algorithms, Data Structures, and Problems - A good collection of keywords definition, and links to further information and implementations.
 
LP Sensitivity Regions - A general methodology for construction of the sensitivity-region is given. Unlike the ordinary sensitivity analysis, the construction presented here allows us to analyze any type of changes including dependent, independent, and multiple changes in both the RHS values and the cost coefficients.
 
Linear Programming FAQs
 
Myths and Counterexamples - Counter-examples to some mathematical statements that seem plausible, it also serves as useful teaching material.
 
NEOS Guide - A guide to optimization including software, and case studies.
 
Nonlinear Programming FAQs
 
OR Tutorial Notes - A set of tutorial notes giving an introduction to operations research from J E Beasley at Imperial College in London.
 
ORCS-L Discussion List - A list to discuss the topics at the interface of OR/MS and Computer Science.
 
Opt-Net Home page - Forum for the optimization community.
 
RGA: Algorithm for Global Optimization - A novel approach to global optimization.
 
The Field of Decision Analysis - Web-based educational and reference materials pertaining to decision analysis.
 
Tools for LP Modeling Validation - This Web site introduces you to what can go wrong in the process of building a linear programming model. Potential problems exist which affect any linear programming application. Solutions may be infeasible or unbounded, or there may be multiple solutions. Degeneracy may also occur. These and other pitfalls are not of much deficiencies of linear programming as they are situations of which the decision maker should be cognizant.
 
Toward the Simplex Method - The web site contains notes on the development of simplex algorithm from the algebraic methods of solving linear programs, together with pivoting row operations needed to perform the simplex iterations.
 
simsoc discussion list - This list is discussion related to the use of computer simulation in the social sciences, including approaches based on micro-simulation and multi-agent modelling.
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