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Description:: Traditionally, robust optimization has solved problems based on static decisions which are predetermined by the decision makers. Once the decisions were made, the problem was solved and whenever a new uncertainty was realized, the uncertainty was incorporated to the original problem and the entire problem was solved again to account...
Keyword:: Adaptive Robust Optimization and Optimization
Creator:: Woo Soo Choe
Owner:: Scholarly Digital Publishing
Date Uploaded:: 11/30/2018
Date Modified:: 11/30/2018

Description:: The chance-constrained method is one of the major approaches to solving optimization problems under various uncertainties. It is a formulation of an optimization problem that ensures that the probability of meeting a certain constraint is above a certain level. In other words, it restricts the feasible region so that the...
Keyword:: Optimization and Chance-constraint method
Creator:: Cristine Li
Owner:: Scholarly Digital Publishing
Date Uploaded:: 11/30/2018
Date Modified:: 11/30/2018

Description:: In this work, we will focus on the “at the same time” or direct transcription approach which allow a simultaneous method for the dynamic optimization problem. In particular, we formulate the dynamic optimization model with orthogonal collocation methods. These methods can also be regarded as a special class of implicit...
Keyword:: Dynamic and Optimization
Creator:: Hanyu Shi
Owner:: Scholarly Digital Publishing
Date Uploaded:: 11/30/2018
Date Modified:: 11/30/2018

Description:: Subgradient Optimization (or Subgradient Method) is an iterative algorithm for minimizing convex functions, used predominantly in Nondifferentiable optimization for functions that are convex but nondifferentiable. It is often slower than Newton's Method when applied to convex differentiable functions, but can be used on convex nondifferentiable functions where Newton's Method will...
Keyword:: Subgradient and Optimization
Creator:: Aaron Anderson
Owner:: Scholarly Digital Publishing
Date Uploaded:: 11/30/2018
Date Modified:: 11/30/2018

Description:: Optimization with absolute values is a special case of linear programming in which a problem made nonlinear due to the presence of absolute values is solved using linear programming methods. Absolute value functions themselves are very difficult to perform standard optimization procedures on. They are not continuously differentiable functions, are...
Keyword:: Absolute Values and Optimization
Creator:: Benjamin Granger, Kathleen Zhou, and Marta Yu
Owner:: Scholarly Digital Publishing
Date Uploaded:: 11/29/2018
Date Modified:: 11/29/2018

Description:: This article concerns the exponential transformation method for globally solving posynomial (or general geometric/signomial) optimization problems with nonconvex objective functions or constraints. A discussion of the method's development and use will be presented.
Keyword:: Exponential Transformation and Optimization
Creator:: Daniel Garcia
Owner:: Scholarly Digital Publishing
Date Uploaded:: 11/29/2018
Date Modified:: 11/29/2018

Description:: Optimization and Game Theory have certain conceptual overlaps. It is even said that John von Neumann conjectured the Duality Theorem using information from his game theory. This article discusses two optimization applications to the game theory: a methodology for solving the Nash Equilibrium and a decentralized model in supply chain...
Keyword:: Game Theory and Optimization
Creator:: Leon Huang
Owner:: Scholarly Digital Publishing
Date Uploaded:: 11/29/2018
Date Modified:: 11/29/2018

Description:: Aerospace collectively represents one of the most sophisticated technological endeavors and largest markets in the world. Coming with substantial costs, nearly every aspect of the industry, from aircraft design to material selection to operation, has been optimized in at least one way. A critical design consideration in any aircraft is...
Keyword:: Wingshape and Optimization
Creator:: Daniel Charles
Owner:: Scholarly Digital Publishing
Date Uploaded:: 11/29/2018
Date Modified:: 11/29/2018

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