Make your home page Add to your favorites  


Help Desk

Site Map


What's New

Search Software:
  MAC Software | Linux Software | Pocket PC | iPod Software | Zune Software
  Software Directories
PC Tools
DVD & Video
MP3 & Audio
Computer Games
Security & AntiVirus
Business Finance
Personal Finance
Database Tools
Personal Managers
Business Managers
Inventory Management
Project Managers
Accounting Tools
Home & Education
Unit Conversion
Word Processing
Presentation Tools

WebCab Optimization for .NET

Refined procedures for solving and performing sensitivity analysis on uni and multi dimensional, local or global optimization problems which may or may not have linear constraints. Specialized Linear programming algorithms based on the Simplex Algorithm and duality are included along with a framework for sensitivity analysis w.r.t. boundaries (duality, or direct approach), or object function coefficients.

Software Information System Requirements
Version: v2.60
  • Windows 9x/NT/2000/XP/2003
  • Pentium II® 500Mhz
  • .NET Framework v1.x
File Size: Full version: 4.19 MB
License:Free to try, $ 179 to buy
Rating :

This suite includes the following features:
  • Local unidimensional optimization - finds global minima / maxima for continuous functions in one dimension
    • Bracketing algorithms - these methods find an interval where at least one extrema of a continuous function exists
      • Acceleration bracketing - this method can be used with any continuous functions
      • Parabolic extrapolation bracketing - gives better results than acceleration bracketing for a large class of functions (functions that are locally parabolic about the extrema)
      • Acceleration bracketing for derivable functions - requires derivatives to be known; it's slower than the general acceleration algorithm but also safer
    • Locate algorithms - these methods converge to the extrema if the extrema is bracketed and the function under consideration is continuous
      • Parabolic interpolation locate - very fast algorithm but with moderate accuracy
      • Linear locate - slow algorithm but exhibits stable convergence
      • Brent locate - medium speed with good accuracy. With a good balance of speed and accuracy, this algorithm is very efficient to use
      • Cubic interpolation locate - very fast algorithm with reasonable accuracy; requires the derivatives to be known
      • Brent method for derivable functions - medium speed and good accuracy but requires derivatives to be known
    • Accurate 'high level' algorithms - these algorithms are easy to use and offer high accuracy but are also very slow compared with the 'low' 'level' algorithms above (1,000 to 10,000 times slower). Use these algorithms when you need reliable results. The probability for a `high level' algorithm to make a mistake is much less than that of `low level' algorithms.
      • Method for continuous functions
      • Method for derivable functions
  • Global unidimensional optimization - finds global minima / maxima.
    • Methods for continuous functions
    • Methods for derivable functions
  • Unconstrained local multidimensional optimization
    • Methods for general functions - these algorithms do not require continuous functions
      • Downhill simplex method of Nelder and Mead - minimizes the function over a sequence of equal volume simplexes
    • Methods for continuous functions - these algorithms require the function to be continuous
      • Conjugate direction algorithms - this algorithm searches by iterating along conjugate paths
        • Powell's method - an implementation of the conjugate direction algorithm
    • Methods for derivable functions - these algorithms require the gradient of the function to be known
      • Steepest descent - a classical method with poor results, this method should mainly be used for testing purposes
      • Conjugate gradient algorithms - speed and accuracy highly dependent on the particular function, these methods can be deceived by 'valleys' in the N-dimensional space
        • Fletcher-Reeves - an implementation of the conjugate gradient method
        • Polak-Riviere - an implementation of the conjugate gradient method
      • Variable metric algorithms/Quasi-Newton algorithms - slow speed; good results on a large class of continuous functions. The basic idea is to find the sequence of matrices which converges to the inverse Hessian of the function.
        • Fletcher-Powell - an implementation of the variable metric algorithm
        • Broyden-Fletcher-Goldfarb-Shanno - an implementation of the variable metric algorithm
  • Unconstrained global multidimensional optimization
    • Simulated annealing - a technique that has attracted significant attention as suitable for optimizing problems of large scale, especially ones where a desired global extremum is hidden among many poorer, local extrema
  • Constrained optimization for derivable functions with linear constraints
    • Rosen's gradient projection algorithm - uses the Kuhn-Tucker conditions as a termination criteria.
  • Linear programming - here the functions are linear and the constraints are linear
    • Simplex algorithm - Kuenzi, Tszchach and Zehnder implementation of the simplex algorithm for linear programming
    • Duality - Construct and solve the dual problem for a given primal linear programming problem.
    • Sensitivity Analysis - Study how the location and value of the extremum varies under perturbations of the object function and parallel shifts of the linear constraints. Sensitivity analysis of the boundaries can very efficient be carried out with the application a duality techniques.
  • Sensitivity Analysis - Stability of the value and location of the extremum
    • General Framework - Perform sensitivity analysis on any optimization problem/algorithm combination.
    • Flexibility - Perform sensitivity analysis on the object function, constraints and/or algorithm.

  • DreamCalc Scientific Calculator
    is the smarter alternative to a hand-held Scientific Calculator for your PC or laptop!

  • King Of Mathermatics
    designed to help people young and old improve there math skills

  • STFMath
    is a multipurpose math utility, suitable not only for students, but also for engineers, professors, or anyone interested in math.

  • Matrix ActiveX Component
    is a useful tool that can simplify the use of matrix operations for mathematical computations in application development.

  • Intel Math Kernel Library for Mac
    is a set of highly optimized, thread-safe, mathematical functions for engineering, scientific and financial applications for Mac.

  • Dynamic Biorhythms
    is an advanced multilingual tool for the analysis, forecast and comparison of biorhythms cycles of any person

  • GrindEQ MathType-to-Equation
    converts MathType objects to Microsoft Equation 2007 or Microsoft Equation 3.x format

  • Global Network Inventory - 50 addresses
    powerful and flexible software and hardware inventory system that can be used as an audit scanner in an agent-free and zero deployment environments

  • Global Mapper 9
    is more than just a viewer capable of displaying the most popular raster, elevation and vector datasets.

  Submit Software | Privacy Policy | Terms of Use | Advertise with Us | Contact Us
 Copyright © All rights reserved.