Multiscale Decision Making
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Multiscale Decision Making
Multiscale decision-making, also referred to as multiscale decision theory (MSDT), is an approach in operations research that combines game theory, multi-agent influence diagrams, in particular dependency graphs, and Markov decision processes to solve multiscale challenges in sociotechnical systems. MSDT considers interdependencies within and between the following scales: system level, time and information. Multiscale decision theory builds upon decision theory and multiscale mathematics. Multiscale decision theory can model and analyze complex decision-making networks that exhibit multiscale phenomena. The theory's results can be used by mechanism designers and decision-makers in organizations and complex systems to improve system performance and decision quality. Multiscale decision theory has been applied to manufacturing enterprise enterprises, service systems, supply chain management, healthcare, systems engineering, among others. In healthcare, for example, MSDT has been used ...
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Operations Research
Operations research ( en-GB, operational research) (U.S. Air Force Specialty Code: Operations Analysis), often shortened to the initialism OR, is a discipline that deals with the development and application of analytical methods to improve decision-making. It is considered to be a subfield of mathematical sciences. The term management science is occasionally used as a synonym. Employing techniques from other mathematical sciences, such as modeling, statistics, and optimization, operations research arrives at optimal or near-optimal solutions to decision-making problems. Because of its emphasis on practical applications, operations research has overlap with many other disciplines, notably industrial engineering. Operations research is often concerned with determining the extreme values of some real-world objective: the maximum (of profit, performance, or yield) or minimum (of loss, risk, or cost). Originating in military efforts before World War II, its techniques have grown to ...
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Complex System
A complex system is a system composed of many components which may interact with each other. Examples of complex systems are Earth's global climate, organisms, the human brain, infrastructure such as power grid, transportation or communication systems, complex software and electronic systems, social and economic organizations (like cities), an ecosystem, a living cell, and ultimately the entire universe. Complex systems are systems whose behavior is intrinsically difficult to model due to the dependencies, competitions, relationships, or other types of interactions between their parts or between a given system and its environment. Systems that are "complex" have distinct properties that arise from these relationships, such as nonlinearity, emergence, spontaneous order, adaptation, and feedback loops, among others. Because such systems appear in a wide variety of fields, the commonalities among them have become the topic of their independent area of research. In many cases, i ...
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Decentralized Decision Making
{{no footnotes, date=June 2016 Decentralized decision-making is any process where the decision-making authority is distributed throughout a larger group. It also connotes a higher authority given to lower level functionaries, executives, and workers. This can be in any organization of any size, from a governmental authority to a corporation. However, the context in which the term is used is generally that of larger organizations. This distribution of power, in effect, has far-reaching implications for the fields of management, organizational behavior, and government. The decisions arising from a process of decentralized decision-making are the functional result of group intelligence and crowd wisdom. Decentralized decision-making also contributes to the core knowledge of group intelligence and crowd wisdom, often in a subconscious way a la Carl Jung's collective unconscious. Decision theory is a method of deductive reasoning based on formal probability and deductive reasoning ...
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Cooperative Distributed Problem Solving
In computing cooperative distributed problem solving is a network of semi-autonomous processing nodes working together to solve a problem, typically in a multi-agent system. That is concerned with the investigation of problem subdivision, sub-problem distribution, results synthesis, optimisation of problem solver coherence and co-ordination. It is closely related to distributed constraint programming and distributed constraint optimization; see the links below. Aspects of CDPS * Neither global control or global data storage – no individual CDPS problem solver (agent) has sufficient information to solve the entire problem. * Control and data are distributed * Communication is slower than computation, therefore: ** Loose coupling between problem solvers ** Efficient protocols (not too much communication overhead) ** problems should be modular, coarse grained * Any unique node is a potential bottleneck ** Organised behaviour is hard to guarantee since no one node has the complete pi ...
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Decision Analysis
Decision analysis (DA) is the discipline comprising the philosophy, methodology, and professional practice necessary to address important decisions in a formal manner. Decision analysis includes many procedures, methods, and tools for identifying, clearly representing, and formally assessing important aspects of a decision; for prescribing a recommended course of action by applying the maximum expected-utility axiom to a well-formed representation of the decision; and for translating the formal representation of a decision and its corresponding recommendation into insight for the decision maker, and other corporate and non-corporate stakeholders. History In 1931, mathematical philosopher Frank Ramsey pioneered the idea of subjective probability as a representation of an individual’s beliefs or uncertainties. Then, in the 1940s, mathematician John von Neumann and economist Oskar Morgenstern developed an axiomatic basis for utility theory as a way of expressing an individual ...
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Multiscale Modeling
Multiscale modeling or multiscale mathematics is the field of solving problems which have important features at multiple scales of time and/or space. Important problems include multiscale modeling of fluids, solids, polymers, proteins, nucleic acids as well as various physical and chemical phenomena (like adsorption, chemical reactions, diffusion). An example of such problems involve the Navier-Stokes equations for incompressible fluid flow. \begin \rho_0(\partial_t\mathbf+(\mathbf\cdot\nabla)\mathbf)=\nabla\cdot\tau, \\ \nabla\cdot\mathbf=0. \end In a wide-variety of applications, the stress tensor \tau is given as a linear function of the gradient \nabla u. Such a choice for \tau has been proven to be sufficient for describing the dynamics of a broad range of fluids. However, it’s use for more complex fluids such as polymers is dubious. In such a case, it may be necessary to use multiscale modeling to accurately model the system such that the stress tensor can be extracted ...
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Virginia Tech
Virginia Tech (formally the Virginia Polytechnic Institute and State University and informally VT, or VPI) is a Public university, public Land-grant college, land-grant research university with its main campus in Blacksburg, Virginia. It also has educational facilities in six regions statewide, a research center in Punta Cana, Dominican Republic, and a study-abroad site in Riva San Vitale, Switzerland. Through its Virginia Tech Corps of Cadets, Corps of Cadets Reserve Officers' Training Corps, ROTC program, Virginia Tech is a United States Senior Military College, senior military college. Virginia Tech offers 280 undergraduate and graduate degree programs to some 34,400 students; as of 2015, it was the state's second-largest public university by enrollment. It manages a research portfolio of $522 million, placing it among the top 50 universities in the U.S. for total research expenditures, top 25 in computer and information sciences and top 10 in engineering, with the latter t ...
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Systems Engineering
Systems engineering is an interdisciplinary field of engineering and engineering management that focuses on how to design, integrate, and manage complex systems over their enterprise life cycle, life cycles. At its core, systems engineering utilizes systems thinking principles to organize this body of knowledge. The individual outcome of such efforts, an engineered system, can be defined as a combination of components that work in synergy to collectively perform a useful Function (engineering), function. Issues such as requirements engineering, reliability, logistics, coordination of different teams, testing and evaluation, maintainability and many other Discipline (academia), disciplines necessary for successful system design, development, implementation, and ultimate decommission become more difficult when dealing with large or complex projects. Systems engineering deals with work-processes, optimization methods, and risk management tools in such projects. It overlaps technical ...
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Healthcare
Health care or healthcare is the improvement of health via the prevention, diagnosis, treatment, amelioration or cure of disease, illness, injury, and other physical and mental impairments in people. Health care is delivered by health professionals and allied health fields. Medicine, dentistry, pharmacy, midwifery, nursing, optometry, audiology, psychology, occupational therapy, physical therapy, athletic training, and other health professions all constitute health care. It includes work done in providing primary care, secondary care, and tertiary care, as well as in public health. Access to health care may vary across countries, communities, and individuals, influenced by social and economic conditions as well as health policies. Providing health care services means "the timely use of personal health services to achieve the best possible health outcomes". Factors to consider in terms of health care access include financial limitations (such as insurance coverage), geo ...
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Supply Chain Management
In commerce, supply chain management (SCM) is the management of the flow of goods and services including all processes that transform raw materials into final products between businesses and locations. This can include the movement and storage of raw materials, work-in-process inventory, finished goods, and end to end order fulfilment from the point of origin to the point of consumption. Interconnected, interrelated or interlinked networks, channels and node businesses combine in the provision of products and services required by end customers in a supply chain. Supply-chain management has been defined as the "design, planning, execution, control, and monitoring of supply chain activities with the objective of creating net value, building a competitive infrastructure, leveraging worldwide logistics, synchronising supply with demand and measuring performance globally". SCM practice draws heavily on industrial engineering, systems engineering, operations management, logis ...
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Service System
A service system (or customer service system, CSS) is a configuration of technology and organizational networks designed to deliver services that satisfy the needs, wants, or aspirations of customers. "Service system" is a term used in the service management, service operations, services marketing, service engineering, and service design literature. While the term frequently appears, it is rarely defined. One definition of a service system is a value coproduction configuration of people, technology, internal and external service systems connected via value propositions, and shared information (language, laws, measures, etc.). The smallest service system is a single person and the largest service system is the world economy. The external service system of the global economy is considered to be ecosystem services. Service systems can be characterized by the value that results from interaction between service systems, whether the interactions are between people, businesses, or n ...
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Mechanism Design
Mechanism design is a field in economics and game theory that takes an objectives-first approach to designing economic mechanisms or incentives, toward desired objectives, in strategic settings, where players act rationally. Because it starts at the end of the game, then goes backwards, it is also called reverse game theory. It has broad applications, from economics and politics in such fields as market design, auction theory and social choice theory to networked-systems (internet interdomain routing, sponsored search auctions). Mechanism design studies solution concepts for a class of private-information games. Leonid Hurwicz explains that 'in a design problem, the goal function is the main "given", while the mechanism is the unknown. Therefore, the design problem is the "inverse" of traditional economic theory, which is typically devoted to the analysis of the performance of a given mechanism.' So, two distinguishing features of these games are: * that a game "designer" choos ...
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