Optimal controlOptimal control theory is a branch of mathematical optimization that deals with finding a control for a dynamical system over a period of time such that an objective function is optimized. It has numerous applications in science, engineering and operations research. For example, the dynamical system might be a spacecraft with controls corresponding to rocket thrusters, and the objective might be to reach the moon with minimum fuel expenditure.
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.
Mathematical optimizationMathematical 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 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.
CompetitionCompetition is a rivalry where two or more parties strive for a common goal which cannot be shared: where one's gain is the other's loss (an example of which is a zero-sum game). Competition can arise between entities such as organisms, individuals, economic and social groups, etc. The rivalry can be over attainment of any exclusive goal, including recognition. Competition occurs in nature, between living organisms which co-exist in the same environment. Animals compete over water supplies, food, mates, and other biological resources.
Perfect competitionIn economics, specifically general equilibrium theory, a perfect market, also known as an atomistic market, is defined by several idealizing conditions, collectively called perfect competition, or atomistic competition. In theoretical models where conditions of perfect competition hold, it has been demonstrated that a market will reach an equilibrium in which the quantity supplied for every product or service, including labor, equals the quantity demanded at the current price. This equilibrium would be a Pareto optimum.
Competition lawCompetition law is the field of law that promotes or seeks to maintain market competition by regulating anti-competitive conduct by companies. Competition law is implemented through public and private enforcement. It is also known as antitrust law (or just antitrust), anti-monopoly law, and trade practices law; the act of pushing for antitrust measures or attacking monopolistic companies (known as trusts) is commonly known as trust busting. The history of competition law reaches back to the Roman Empire.
Competition (economics)In economics, competition is a scenario where different economic firms are in contention to obtain goods that are limited by varying the elements of the marketing mix: price, product, promotion and place. In classical economic thought, competition causes commercial firms to develop new products, services and technologies, which would give consumers greater selection and better products. The greater the selection of a good is in the market, the lower prices for the products typically are, compared to what the price would be if there was no competition (monopoly) or little competition (oligopoly).
Monopolistic competitionMonopolistic competition is a type of imperfect competition such that there are many producers competing against each other, but selling products that are differentiated from one another (e.g. by branding or quality) and hence are not perfect substitutes. In monopolistic competition, a company takes the prices charged by its rivals as given and ignores the impact of its own prices on the prices of other companies. If this happens in the presence of a coercive government, monopolistic competition will fall into government-granted monopoly.
Program optimizationIn computer science, program optimization, code optimization, or software optimization, is the process of modifying a software system to make some aspect of it work more efficiently or use fewer resources. In general, a computer program may be optimized so that it executes more rapidly, or to make it capable of operating with less memory storage or other resources, or draw less power. Although the word "optimization" shares the same root as "optimal", it is rare for the process of optimization to produce a truly optimal system.
Convex optimizationConvex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets (or, equivalently, maximizing concave functions over convex sets). Many classes of convex optimization problems admit polynomial-time algorithms, whereas mathematical optimization is in general NP-hard.
Competition (biology)Competition is an interaction between organisms or species in which both require a resource that is in limited supply (such as food, water, or territory). Competition lowers the fitness of both organisms involved since the presence of one of the organisms always reduces the amount of the resource available to the other. In the study of community ecology, competition within and between members of a species is an important biological interaction.
Kernel (operating system)The kernel is a computer program at the core of a computer's operating system and generally has complete control over everything in the system. It is the portion of the operating system code that is always resident in memory and facilitates interactions between hardware and software components. A full kernel controls all hardware resources (e.g. I/O, memory, cryptography) via device drivers, arbitrates conflicts between processes concerning such resources, and optimizes the utilization of common resources e.
Feasible regionIn mathematical optimization, a feasible region, feasible set, search space, or solution space is the set of all possible points (sets of values of the choice variables) of an optimization problem that satisfy the problem's constraints, potentially including inequalities, equalities, and integer constraints. This is the initial set of candidate solutions to the problem, before the set of candidates has been narrowed down.
Separation of mechanism and policyThe separation of mechanism and policy is a design principle in computer science. It states that mechanisms (those parts of a system implementation that control the authorization of operations and the allocation of resources) should not dictate (or overly restrict) the policies according to which decisions are made about which operations to authorize, and which resources to allocate. While most commonly discussed in the context of security mechanisms (authentication and authorization), separation of mechanism and policy is applicable to a range of resource allocation problems (e.
Interspecific competitionInterspecific competition, in ecology, is a form of competition in which individuals of different species compete for the same resources in an ecosystem (e.g. food or living space). This can be contrasted with mutualism, a type of symbiosis. Competition between members of the same species is called intraspecific competition. If a tree species in a dense forest grows taller than surrounding tree species, it is able to absorb more of the incoming sunlight.
Interprocedural optimizationInterprocedural optimization (IPO) is a collection of compiler techniques used in computer programming to improve performance in programs containing many frequently used functions of small or medium length. IPO differs from other compiler optimizations by analyzing the entire program as opposed to a single function or block of code. IPO seeks to reduce or eliminate duplicate calculations and inefficient use of memory and to simplify iterative sequences such as loops.
Optimizing compilerIn computing, an optimizing compiler is a compiler that tries to minimize or maximize some attributes of an executable computer program. Common requirements are to minimize a program's execution time, memory footprint, storage size, and power consumption (the last three being popular for portable computers). Compiler optimization is generally implemented using a sequence of optimizing transformations, algorithms which take a program and transform it to produce a semantically equivalent output program that uses fewer resources or executes faster.
Batch processingComputerized batch processing is a method of running software programs called jobs in batches automatically. While users are required to submit the jobs, no other interaction by the user is required to process the batch. Batches may automatically be run at scheduled times as well as being run contingent on the availability of computer resources. The term "batch processing" originates in the traditional classification of methods of production as job production (one-off production), batch production (production of a "batch" of multiple items at once, one stage at a time), and flow production (mass production, all stages in process at once).
History of operating systemsComputer operating systems (OSes) provide a set of functions needed and used by most application programs on a computer, and the links needed to control and synchronize computer hardware. On the first computers, with no operating system, every program needed the full hardware specification to run correctly and perform standard tasks, and its own drivers for peripheral devices like printers and punched paper card readers. The growing complexity of hardware and application programs eventually made operating systems a necessity for everyday use.
Numerical linear algebraNumerical linear algebra, sometimes called applied linear algebra, is the study of how matrix operations can be used to create computer algorithms which efficiently and accurately provide approximate answers to questions in continuous mathematics. It is a subfield of numerical analysis, and a type of linear algebra. Computers use floating-point arithmetic and cannot exactly represent irrational data, so when a computer algorithm is applied to a matrix of data, it can sometimes increase the difference between a number stored in the computer and the true number that it is an approximation of.
