Linear programmingLinear programming (LP), also called linear optimization, is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships. Linear programming is a special case of mathematical programming (also known as mathematical optimization). More formally, linear programming is a technique for the optimization of a linear objective function, subject to linear equality and linear inequality constraints.
Nonlinear programmingIn mathematics, nonlinear programming (NLP) is the process of solving an optimization problem where some of the constraints or the objective function are nonlinear. An optimization problem is one of calculation of the extrema (maxima, minima or stationary points) of an objective function over a set of unknown real variables and conditional to the satisfaction of a system of equalities and inequalities, collectively termed constraints. It is the sub-field of mathematical optimization that deals with problems that are not linear.
Three Laws of RoboticsThe Three Laws of Robotics (often shortened to The Three Laws or Asimov's Laws) are a set of rules devised by science fiction author Isaac Asimov, which were to be followed by robots in several of his stories. The rules were introduced in his 1942 short story "Runaround" (included in the 1950 collection I, Robot), although similar restrictions had been implied in earlier stories. The Three Laws, presented to be from the fictional "Handbook of Robotics, 56th Edition, 2058 A.D.
Constraint (mathematics)In mathematics, a constraint is a condition of an optimization problem that the solution must satisfy. There are several types of constraints—primarily equality constraints, inequality constraints, and integer constraints. The set of candidate solutions that satisfy all constraints is called the feasible set. The following is a simple optimization problem: subject to and where denotes the vector (x1, x2). In this example, the first line defines the function to be minimized (called the objective function, loss function, or cost function).
Isobel Miller KuhnIsobel Selina Miller Kuhn, born Isobel Selina Miller, aka, "Belle" (December 17, 1901 – March 20, 1957), known as Isobel Kuhn, was a Canadian Christian missionary to the Lisu people of Yunnan Province, China, and northern Thailand. She served with the China Inland Mission, along with her husband, John, as a Bible translator, church planter, Bible teacher, evangelist and authored nine books about her experiences. Isobel Selina Miller was born in Toronto, Ontario, Canada, and moved with her family to Vancouver, British Columbia, when she was eleven years old.
Ellipsoid methodIn mathematical optimization, the ellipsoid method is an iterative method for minimizing convex functions. When specialized to solving feasible linear optimization problems with rational data, the ellipsoid method is an algorithm which finds an optimal solution in a number of steps that is polynomial in the input size. The ellipsoid method generates a sequence of ellipsoids whose volume uniformly decreases at every step, thus enclosing a minimizer of a convex function. The ellipsoid method has a long history.
Digital Signal 1Digital Signal 1 (DS1, sometimes DS-1) is a T-carrier signaling scheme devised by Bell Labs. DS1 is the primary digital telephone standard used in the United States, Canada and Japan and is able to transmit up to 24 multiplexed voice and data calls over telephone lines. E-carrier is used in place of T-carrier outside the United States, Canada, Japan, and South Korea. DS1 is the logical bit pattern used over a physical T1 line; in practice, the terms DS1 and T1 are often used interchangeably.
Optimization problemIn mathematics, computer science and economics, an optimization problem is the problem of finding the best solution from all feasible solutions. Optimization problems can be divided into two categories, depending on whether the variables are continuous or discrete: An optimization problem with discrete variables is known as a discrete optimization, in which an object such as an integer, permutation or graph must be found from a countable set.
Global optimizationGlobal optimization is a branch of applied mathematics and numerical analysis that attempts to find the global minima or maxima of a function or a set of functions on a given set. It is usually described as a minimization problem because the maximization of the real-valued function is equivalent to the minimization of the function . Given a possibly nonlinear and non-convex continuous function with the global minima and the set of all global minimizers in , the standard minimization problem can be given as that is, finding and a global minimizer in ; where is a (not necessarily convex) compact set defined by inequalities .
Jeff KuhnJeffrey Richard Kuhn, also known as Jeff Kuhn, is an American physicist and astronomer who is a professor of astronomy at the University of Hawaii. He is known for his contributions to astrophysics and the search for extraterrestrial life, particularly in the areas of telescope and detection system development, the study of the Sun and its corona, and the search for planets around other stars.
2018 St. Louis Cardinals seasonThe 2018 St. Louis Cardinals season was the 137th for the St. Louis Cardinals of Major League Baseball (MLB), a franchise in St. Louis, Missouri. It was the 127th season for the Cardinals in the National League (NL), and their 13th at Busch Stadium III. Forbes ranked the Cardinals as the seventh-highest valued team of the 30 teams in 2017 for its 1.9billionvaluation(+6319 million revenue, and $40 million operating income. The Cardinals also had baseball's second-highest local television rating, averaging 7. Gajski–Kuhn chartThe Gajski–Kuhn chart (or Y diagram) depicts the different perspectives in VLSI hardware design. Mostly, it is used for the development of integrated circuits. Daniel Gajski and Robert Kuhn developed it in 1983. In 1985, Robert Walker and Donald Thomas refined it. According to this model, the development of hardware is perceived within three domains that are depicted as three axis and produce a Y. Along these axis, the abstraction levels that describe the degree of abstraction.
