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Bilevel Optimization
Bilevel optimization is a special kind of optimization where one problem is embedded (nested) within another. The outer optimization task is commonly referred to as the upper-level optimization task, and the inner optimization task is commonly referred to as the lower-level optimization task. These problems involve two kinds of variables, referred to as the upper-level variables and the lower-level variables. Mathematical formulation of the problem A general formulation of the bilevel optimization problem can be written as follows: \min\limits_\;\; F(x,y) subject to: G_i(x,y) \leq 0, for i \in \ y \in \arg \min \limits_ \ where : F,f: R^ \times R^ \to R : G_i,g_j: R^ \times R^ \to R : X \subseteq R^ : Y \subseteq R^. In the above formulation, F represents the upper-level objective function and f represents the lower-level objective function. Similarly x represents the upper-level decision vector and y represents the lower-level decision vector. G_i and g_j represent the ...
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Optimization
Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems of sorts arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries. In the more general approach, an optimization problem consists of maxima and minima, maximizing or minimizing a Function of a real variable, real function by systematically choosing Argument of a function, input values from within an allowed set and computing the Value (mathematics), value of the function. The generalization of optimization theory and techniques to other formulations constitutes a large area of applied mathematics. More generally, opti ...
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Extended Mathematical Programming (EMP)
Algebraic modeling languages like AIMMS, AMPL, GAMS, MPL and others have been developed to facilitate the description of a problem in mathematical terms and to link the abstract formulation with data-management systems on the one hand and appropriate algorithms for solution on the other. Robust algorithms and modeling language interfaces have been developed for a large variety of mathematical programming problems such as linear programs (LPs), nonlinear programs (NPs), Mixed Integer Programs (MIPs), mixed complementarity programs (MCPs) and others. Researchers are constantly updating the types of problems and algorithms that they wish to use to model in specific domain applications. Extended Mathematical Programming (EMP) is an extension to algebraic modeling languages that facilitates the automatic reformulation of new model types by converting the EMP model into established mathematical programming classes to solve by mature solver algorithms. A number of important problem clas ...
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Differentiability
In mathematics, a differentiable function of one real variable is a function whose derivative exists at each point in its domain. In other words, the graph of a differentiable function has a non-vertical tangent line at each interior point in its domain. A differentiable function is smooth (the function is locally well approximated as a linear function at each interior point) and does not contain any break, angle, or cusp. If is an interior point in the domain of a function , then is said to be ''differentiable at'' if the derivative f'(x_0) exists. In other words, the graph of has a non-vertical tangent line at the point . is said to be differentiable on if it is differentiable at every point of . is said to be ''continuously differentiable'' if its derivative is also a continuous function over the domain of the function f. Generally speaking, is said to be of class if its first k derivatives f^(x), f^(x), \ldots, f^(x) exist and are continuous over the domain of the func ...
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Discrete Group
In mathematics, a topological group ''G'' is called a discrete group if there is no limit point in it (i.e., for each element in ''G'', there is a neighborhood which only contains that element). Equivalently, the group ''G'' is discrete if and only if its identity is isolated. A subgroup ''H'' of a topological group ''G'' is a discrete subgroup if ''H'' is discrete when endowed with the subspace topology from ''G''. In other words there is a neighbourhood of the identity in ''G'' containing no other element of ''H''. For example, the integers, Z, form a discrete subgroup of the reals, R (with the standard metric topology), but the rational numbers, Q, do not. Any group can be endowed with the discrete topology, making it a discrete topological group. Since every map from a discrete space is continuous, the topological homomorphisms between discrete groups are exactly the group homomorphisms between the underlying groups. Hence, there is an isomorphism between the category of ...
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Non-linearity
In mathematics and science, a nonlinear system is a system in which the change of the output is not proportional to the change of the input. Nonlinear problems are of interest to engineers, biologists, physicists, mathematicians, and many other scientists because most systems are inherently nonlinear in nature. Nonlinear dynamical systems, describing changes in variables over time, may appear chaotic, unpredictable, or counterintuitive, contrasting with much simpler linear systems. Typically, the behavior of a nonlinear system is described in mathematics by a nonlinear system of equations, which is a set of simultaneous equations in which the unknowns (or the unknown functions in the case of differential equations) appear as variables of a polynomial of degree higher than one or in the argument of a function which is not a polynomial of degree one. In other words, in a nonlinear system of equations, the equation(s) to be solved cannot be written as a linear combination of the un ...
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Relaxation (approximation)
In mathematical optimization and related fields, relaxation is a modeling strategy. A relaxation is an approximation of a difficult problem by a nearby problem that is easier to solve. A solution of the relaxed problem provides information about the original problem. For example, a linear programming relaxation of an integer programming problem removes the integrality constraint and so allows non-integer rational solutions. A Lagrangian relaxation of a complicated problem in combinatorial optimization penalizes violations of some constraints, allowing an easier relaxed problem to be solved. Relaxation techniques complement or supplement branch and bound algorithms of combinatorial optimization; linear programming and Lagrangian relaxations are used to obtain bounds in branch-and-bound algorithms for integer programming. The modeling strategy of relaxation should not be confused with iterative methods of relaxation, such as successive over-relaxation (SOR); iterative methods of ...
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Slater's Condition
In mathematics, Slater's condition (or Slater condition) is a sufficient condition for strong duality to hold for a convex optimization problem, named after Morton L. Slater. Informally, Slater's condition states that the feasible region must have an interior point (see technical details below). Slater's condition is a specific example of a constraint qualification. In particular, if Slater's condition holds for the primal problem, then the duality gap is 0, and if the dual value is finite then it is attained. Formulation Consider the optimization problem : \text\; f_0(x) : \text\ :: f_i(x) \le 0 , i = 1,\ldots,m :: Ax = b where f_0,\ldots,f_m are convex functions. This is an instance of convex programming. In words, Slater's condition for convex programming states that strong duality holds if there exists an x^* such that x^* is strictly feasible (i.e. all constraints are satisfied and the nonlinear constraints are satisfied with strict inequalities). Mathematically, Sla ...
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Strategic Offensive
An offensive is a military operation that seeks through an aggressive projection of armed forces to occupy territory, gain an objective or achieve some larger strategic, operational, or tactical goal. Another term for an offensive often used by the media is "invasion", or the more general "attack". An offensive is a conduct of combat operations that seek to achieve only some of the objectives of the strategy being pursued in the theatre as a whole. Commonly an offensive is carried out by one or more divisions, numbering between 10 and 30,000 troops as part of a combined arms manoeuvre. The offensive was considered a pre-eminent means of producing victory, although with the recognition of a defensive phase at some stage of the execution. A quick guide to the size or scope of the offensive is to consider the number of troops involved in the side initiating the offensive. Offensives are largely conducted as a means to secure initiative in a confrontation between opponents. They ...
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Heinrich Freiherr Von Stackelberg
Heinrich Freiherr von Stackelberg (October 31, 1905 – October 12, 1946) was a Nazi economist who contributed to game theory and industrial organization and is known for the Stackelberg leadership model. Stackelberg became a member of the Nazi Party in 1931 and was a Scharführer (Sergeant) in the SS. However, his interactions with many German aristocrats opposed to the Nazi regime (some of whom were within his immediate family), led to his increased disillusionment with that movement to the extent that towards the end of his life he no longer supported it. Biography Stackelberg was born in Moscow into a Baltic German family of nobility from present-day Estonia. His mother was an Argentinian of Spanish descent. After the October Revolution the family fled to Germany, first to Ratibor and later to Cologne. He studied economics and mathematics at the University of Cologne as an undergraduate. He graduated in 1927 with a thesis on the Quasi-rent in Alfred Marshalls work (german ...
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Mathematical Programming With Equilibrium Constraints
Mathematical programming with equilibrium constraints (MPEC) is the study of constrained optimization problems where the constraints include variational inequalities or complementarities. MPEC is related to the Stackelberg game. MPEC is used in the study of engineering design, economic equilibrium, and multilevel games. MPEC is difficult to deal with because its feasible region is not necessarily convex or even connected Connected may refer to: Film and television * ''Connected'' (2008 film), a Hong Kong remake of the American movie ''Cellular'' * '' Connected: An Autoblogography About Love, Death & Technology'', a 2011 documentary film * ''Connected'' (2015 TV .... References * Z.-Q. Luo, J.-S. Pang and D. Ralph: ''Mathematical Programs with Equilibrium Constraints''. Cambridge University Press, 1996, . * B. Baumrucker, J. Renfro, L. T. Biegler, MPEC problem formulations and solution strategies with chemical engineering applications, Computers & Chemical Engineering, ...
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