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- Description:
- The term Connected Vehicle (CV) is broadly used to identify any ‘smart vehicle’ with wireless connectivity to the roadside infrastructure and other vehicles. CVs that can be driven autonomously are called connected autonomous vehicles (CAVs). With real-time communication and data transmission capability, CAVs have the potential to improve the transportation...
- Keyword:
- signal control, automated vehicles, travel time reliability, traffic flow theory, connected vehicles, and simulation
- Subject:
- Civil and Environmental Engineering and Robert R. McCormick School of Engineering and Applied Science
- Creator:
- Archak Mittal
- Owner:
- amz734
- Date Uploaded:
- 11/28/2018
- Date Modified:
- 11/29/2018
- Date Created:
- 2018
- Resource Type:
- Dissertation
-
- 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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- 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
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- 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
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- Description:
- Logarithmic transformation is a method used to change geometric programs into their convex forms. A geometric program, or GP, is a type of global optimization problem that concerns minimizing a subject to constraint functions so as to allow one to solve unique non-linear programming problems. All geometric programs contain functions...
- Keyword:
- Logarithmic and Transformation
- Creator:
- Hassan Ali
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
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- Description:
- McCormick Envelopes are a type of convex relaxation used in bilinear Non Linear Programming problems. Many times these envelopes are used to solve a Mixed Integer Non Linear Programming problem by relaxing the MINLP problem so that it becomes a convex NLP. Solving this convex NLP will provide a lower...
- Keyword:
- Global Optimization and McCormick
- Creator:
- John Dombrowski
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
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- Keyword:
- Linear Approximation, Optimization, and Piecewise
- Creator:
- John Marsiglio
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
-
- Description:
- Spatial branch-and-bound is a divide-and-conquer technique used to find the deterministic solution of global optimization problems.1 It is a type of branch-and-bound method, which solves for the set of parameters that globally optimize the objective function, whether that be finding the minimum or maximum value of or , respectively, where...
- Keyword:
- Bound and Spatial Branch
- Creator:
- Ellen Zhuang
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
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- Description:
- Computational complexity refers to the amount of resources required to solve a type of problem by systematic application of an algorithm. Resources that can be considered include the amount of communications, gates in a circuit, or the number of processors. Because the size of the particular input to a problem...
- Keyword:
- Computational and Complexity
- Creator:
- David O'Brien, Mark Caswell, and David Chen
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
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- Description:
- The objective of game theory is to analyze the relationship between decision-making situations in order to achieve a desirable outcome. The theory can be applied to a wide range of applications, including, but not limited to, economics, politics and even the biological sciences. In essence, game theory serves as means...
- Keyword:
- Game Theory, Matrices, and Matrix
- Creator:
- Matt Kweon and Nick Dotzenrod
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
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- Description:
- Network Flow Optimization problems form the most special class of linear programming problems. Transportation, electric, and communication networks are clearly common applications of Network Optimization. These types of problems can be viewed as minimizing transportation problems. This Network problem will include cost of moving materials through a network involving varying...
- Keyword:
- Network Flow and Linear Programming
- Creator:
- Aaron Frank, Blake Alexander, and Joshua Lee
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
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- Description:
- Interior point methods are a type of algorithm that are used in solving both linear and nonlinear convex optimization problems that contain inequalities as constraints. The LP Interior-Point method relies on having a linear programming model with the objective function and all constraints being continuous and twice continuously differentiable. In...
- Keyword:
- Interior Point
- Creator:
- John Plaxco, Alex Valdes, and Wojciech Stojko
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
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- 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
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- Description:
- Facility location problems deal with selecting the placement of a facility (often from a list of integer possibilities) to best meet the demanded constraints. The problem often consists of selecting a factory location that minimizes total weighted distances from suppliers and customers, where weights are representative of the difficulty of...
- Keyword:
- Mixed-Integer Linear Programming and Facility
- Creator:
- Aaron Litoff
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
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- Description:
- The traveling salesman problem (TSP) is a widely studied combinatorial optimization problem, which, given a set of cities and a cost to travel from one city to another, seeks to identify the tour that will allow a salesman to visit each city only once, starting and ending in the same...
- Keyword:
- Game Theory and Travelling Salesman
- Creator:
- Jessica Yu
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
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- Description:
- Mixed-integer cuts or Cutting-plane methods is an iterative approach used to simplify the solution of a mixed integer linear programming (MILP) problem. Cutting-plane methods work by first relaxing the MILP to a complementary linear programming problem and cutting the feasible region to narrow down the solution search space to only...
- Keyword:
- Mixed-integer and linear programming
- Creator:
- Tahir Kapoor
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
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- Description:
- A disjunctive inequality is a type of constraint that exists in mixed integer linear programming (MILP) and mixed integer nonlinear programming (MINLP) problems. It involves constraining a solution space with multiple inequalities or sets of inequalities related by an OR statement. This "OR" statement must then be reformulated using one...
- Keyword:
- Disjunctive inequalities
- Creator:
- Camille Bilodeau
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
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- Description:
- Lagrangian duality theory refers to a way to find a bound or solve an optimization problem (the primal problem) by looking at a different optimization problem (the dual problem). More specifically, the solution to the dual problem can provide a bound to the primal problem or the same optimal solution...
- Keyword:
- Lagrangian and Duality
- Creator:
- Hannah Seo
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/30/2018
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- Description:
- Column generation algorithms are used for MILP problems. The formulation was initially proposed by Ford and Fulkerson in 1958 . The main advantage of column generation is that not all possibilities need to be enumerated. Instead, the problem is first formulated as a restricted master problem (RMP). This RMP has...
- Keyword:
- Column Generations and Algorithms
- Creator:
- Kedric Daly
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
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- Description:
- A heuristic algorithm is one that is designed to solve a problem in a faster and more efficient fashion than traditional methods by sacrificing optimality, accuracy, precision, or completeness for speed. Heuristic algorithms often times used to solve NP-complete problems, a class of decision problems. In these problems, there is...
- Keyword:
- Heuristic
- Creator:
- Vincent Kenny, Matthew Nathal, and Spencer Saldana
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
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- Description:
- Branch and cut method is a very successful algorithm for solving a variety of integer programming problems, and it also can provide a guarantee of optimality. Many problems involve variables which are not continuous but instead have integer values, and they can be solved by branch-and cut method. This method...
- Keyword:
- Cut, Mixed-Linear Programming, and Branch
- Creator:
- YenChieh Chou
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/29/2018
- Date Modified:
- 11/29/2018
-
- Description:
- Sigmoid problems are a class of optimization problems with the objective of maximizing the sum of multiple sigmoid functions. They are defined by their limits at negative and positive infinity. Similar to the unit step function the function approaches 1 as it approaches infinity and approaches -1 as it approaches...
- Keyword:
- Signomial
- Creator:
- Matthew Hantzmon
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
-
- Description:
- Mixed-integer linear fractional programming (MILFP) is a category of mixed-integer linear programming (MILP). It is similar to MILP in that it uses the branch and bound approach. It is widely used in process engineering for optimizing a wide variety of production processes ranging from petroleum refinery to polymerization processses and...
- Keyword:
- Fractional Programming
- Creator:
- Ho-Hyun Sun
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
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- Description:
- The generalized disjunctive programming (GDP) was first introduced by Raman and Grossman (1994). The GDP extends the use of (linear) disjunctive programming (Balas, 1985) into mixed-integer nonlinear programming (MINLP) problems, and hence the name. The GDP enables programmers to solve the MINLP/MILP optimization problems by applying a combination of algebraic...
- Keyword:
- Convex and Disjunct
- Creator:
- Yunjie Wang
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
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- Description:
- General disjunctive programming, GDP, is an alternative approach to represent the formulation of traditional Mixed-Integer Nonlinear Programming, solving discrete/continuous optimization problems. By using algebraic constraints, disjunctions and logic propositions, Boolean and continuous variables are involved in the GDP formulation. The formulation process of GDP problem are more intuitive, and the...
- Keyword:
- Generalized disjunctive programming (GDP) and Nonconvex
- Creator:
- Kaiwen Li
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
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- Description:
- The Branch and Bound (BB or B&B) algorithm is first proposed by A. H. Land and A. G. Doig in 1960 for discrete programming. It is a general algorithm for finding optimal solutions of various optimization problems, especially in discrete and combinatorial optimization. A branch and bound algorithm consists of...
- Keyword:
- Branch and Bound
- Creator:
- Jiyao Gao
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
-
- Description:
- The organization of general design problems into programming models allows for the defining and finding of their (global) optimal solution. MINLP models represent problems as a sets of continuous variables with binary integer variables. The continuous variables are restricted to defined constraints, and the binary variables represent whether or not...
- Keyword:
- MINLP and Branch
- Creator:
- Pear Dhiantravan
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
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- Description:
- J.F. Benders devised an approach for exploiting the structure of mathematical programming problems with complicating variables (variables which, when temporarily fixed, render the remaining optimization problem considerably more tractable).The algorithm he proposed for finding the optimal value of this vector employs a cutting-plane approach for building up adequate representations of...
- Keyword:
- Generalized
- Creator:
- Yuanxi Zhao
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
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- Description:
- Outer approximation is a basic approach for solving Mixed Integer Nonlinear Programming (MINLP) models suggested by Duran and Grossmann (1986) . Based on principles of decomposition, outer-approximation and relaxation, the proposed algorithm effectively exploits the structure of the original problems. The new problems consist of solving an alternating finite sequence...
- Keyword:
- Outer-approximaton and Programming
- Creator:
- Xudan Sha
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
-
- Description:
- Extended Cutting Plane is an optimization method suggested by Westerlund and Petersson in 1996 to solve Mixed-Integer NonLinear Programming (MINLP) problems . ECP can be thought as an extension of Kelley's cutting plane method, which uses iterative Newton's method to refine feasible area and ultimately solve a problem within tolerable...
- Keyword:
- Extended cutting place
- Creator:
- Kyung Je Lee
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
-
- Description:
- An algorithm is a line search method if it seeks the minimum of a defined nonlinear function by selecting a reasonable direction vector that, when computed iteratively with a reasonable step size, will provide a function value closer to the absolute minimum of the function. Varying these will change the...
- Keyword:
- Line Search Methods
- Creator:
- Elizabeth Conger
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
-
- Description:
- Trust-region method (TRM) is one of the most important numerical optimization methods in solving nonlinear programming (NLP) problems. It works in a way that first define a region around the current best solution, in which a certain model (usually a quadratic model) can to some extent approximate the original objective...
- Keyword:
- programming and Trust-region
- Creator:
- Wenhe (Wayne) Ye
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
-
- Description:
- The interior point (IP) method for nonlinear programming was pioneered by Anthony V. Fiacco and Garth P. McCormick in the early 1960s. The basis of IP method restricts the constraints into the objective function (duality ( http://en.wikipedia.org/wiki/Duality_%28optimization%29) ) by creating a barrier function. This limits potential solutions to iterate in only...
- Keyword:
- Interior Point
- Creator:
- Cindy Chen
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
-
- Description:
- The conjugate gradient method is a mathematical technique that can be useful for the optimization of both linear and non-linear systems. This technique is generally used as an iterative algorithm, however, it can be used as a direct method, and it will produce a numerical solution. Generally this method is...
- Keyword:
- Conjugate Gradient Methods
- Creator:
- Erik Zuehlke
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
-
- Description:
- Quasi-Newton Methods (QNMs) are generally a class of optimization methods that are used in Non-Linear Programming when full Newton’s Methods are either too time consuming or difficult to use. More specifically, these methods are used to find the global minimum of a function f(x) that is twice-differentiable. There are distinct...
- Keyword:
- Quasi-Newton
- Creator:
- Vincent Cericola
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
-
- Description:
- Quadratic programming (QP) is the problem of optimizing a quadratic objective function and is one of the simplests form of non-linear programming. The objective function can contain bilinear or up to second order polynomial terms, and the constraints are linear and can be both equalities and inequalities. QP is widely...
- Keyword:
- Quadratic Programming
- Creator:
- Jack Heider
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
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- Description:
- Sequential quadratic programming (SQP) is a class of algorithms for solving non-linear optimization problems (NLP) in the real world. It is powerful enough for real problems because it can handle any degree of non-linearity including non-linearity in the constraints. The main disadvantage is that the method incorporates several derivatives, which...
- Keyword:
- Sequential Quadratic Programming
- Creator:
- Ben Goodman
- 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
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- Keyword:
- equilibrium and Mathematical Programming
- Creator:
- Alexandra Rodriguez and Brandon Muncy
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
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- 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:
- Geometric programming was introduced in 1967 by Duffin, Peterson and Zener. It is very useful in the applications of a variety of optimization problems, and falls under the general class of signomial problems[1]. It can be used to solve large scale, practical problems by quantifying them into a mathematical optimization...
- Keyword:
- Geometric Programming
- Creator:
- Helen Wu
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
-
- Description:
- Non-differentiable optimization is a category of optimization that deals with objective that for a variety of reasons is non differentiable and thus non-convex. The functions in this class of optimization are generally non-smooth. These functions although continuous often contain sharp points or corners that do not allow for the solution...
- Keyword:
- Differentiation Optimization
- Creator:
- Nathanael Robinson
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
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- Keyword:
- Stochastic
- Creator:
- Jake Heggestad
- 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:
- Fuzzy programming is one of many optimization models that deal with optimization under uncertainty. This model can be applied when situations are not clearly defined and thus have uncertainty, or an exact value is not critical to the problem. For example, categorizing people into young, middle aged and old is...
- Keyword:
- Fuzzy Programming
- Creator:
- Irina Baek
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
-
- Description:
- Robust optimization is a subset of optimization theory that deals with a certain measure of robustness vs uncertainty. This balance of robustness and uncertainty is represented as variability in the parameters of the problem at hand and or its solution [1]. In robust optimization, the modeler aims to find decisions...
- Keyword:
- Robust and Classical Optimization
- Creator:
- Andre Ramirez-Cedeno
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 11/30/2018
-
- 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:
- Robust optimization is a distinct approach to optimizations problems that allows for the incorporation of uncertainty. The usefulness of robust optimization lies in the ability to solve for every realization of the uncertain parameters. As a result, the problem can be solved for the worst-case scenarios of the entire set...
- Keyword:
- Data Driven
- Creator:
- Watson Fu
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 11/30/2018
- Date Modified:
- 12/04/2018
-
- Description:
- Patrick F. Quinn states that Edgar Allan Poe wrote poems at an age “too young to have any knowledge of the world but from his own breast,” and attributes Poe’s decision to leave flaws in his “smaller pieces” intact to “[fondness fostered by] his old age” (Quinn 9). While readers...
- Keyword:
- Egyptian "Book of the Dead", Prose, Edgar Allan Poe, and Poetry
- Creator:
- Lydia E. Wuorinen
- Owner:
- Lydia Elizabeth Wuorinen
- Date Uploaded:
- 12/02/2018
- Date Modified:
- 12/03/2018
- Date Created:
- 2018
- Resource Type:
- Research Paper
-
- Description:
- Recent advances in cell-free gene expression (CFE) systems have enabled their use for a host of synthetic biology applications, particularly for rapid prototyping of genetic circuits and biosensors. Despite the proliferation of cell-free protein synthesis platforms, the large number of currently existing protocols for making CFE extracts muddles the collective...
- Keyword:
- cell-free synthetic biology, TX-TL, CFE, cell extract, genetic circuitry, in vitro protein synthesis, CFPS, and endogenous transcription
- Subject:
- Synthetic biology and Genetic regulation
- Creator:
- Nancy Kelley-Loughnane, Michael C. Jewett, Julius B. Lucks, and Adam D. Silverman
- Owner:
- Julius Beau Lucks
- Publisher:
- American Chemical Society
- Language:
- English
- Date Uploaded:
- 12/14/2018
- Date Modified:
- 01/07/2020
- Date Created:
- 12/14/18
- Resource Type:
- Dataset