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One of the most important steps in optimization is formulating well-posed and meaningful problems that you can interpret ...

Multiobjective optimization is somewhat of a misnomer -- you actually have to have predefined weightings for each of the ...

A system is converged when the residuals are close to 0 within a tolerance. How this is achieved depends on what solver you use, ...

Week 5: Lecture 09C: Linear Programming Problems.

Tony from SVSU Micro Math helps you solve a linear programming problem using a graphical method. Problem: Maximize ...

Welcome to 'Introduction to System Dynamics Modeling' course ! This lecture covers modeling non-linear relationships using ...

Week 6: Lecture 12C: Proof of strong duality (continued)

The fundamental theorem of linear programming states the following: for any given linear programming problem, exactly one of ...

There are many ways to compute partial derivatives: finite-differencing, complex-step, analytically by hand, or through algorithmic ...

Welcome to 'Introduction to System Dynamics Modeling' course ! This lecture continues the discussion on table functions, ...

Tony from SVSU Micro Math helps you solve a linear programming problem using a graphical method. Problem: Minimize C=2x+y ...

Week 7: Lecture 13A: Farkas' lemma.

Week 5: Lecture 10A: Extreme points and optimal solution of an LP.

Qualitative data analysis and quantitative data analysis differ significantly in their approach. Quantitative research is more ...

Professor Patrick Sturgis, NCRM director, in the first (of three) part of the Structural Equiation Modeling NCRM online course.

Part of MIP2020 online workshop: https://sites.google.com/view/mipworkshop2020/home Poster Session 4: Stochastic ...

Dynamic Data Assimilation: an introduction by Prof S. Lakshmivarahan,School of Computer Science,University of Oklahoma.

In this case, we have a formula for it. Later, we'll use forces and information about springs to solve for this, but at the moment I'm ...