[TOC]
↗ Decision Theory & Decision Analysis ↗ Mathematical Modeling & Abstraction ↗ Models of Computation & Abstract Machines
↗ Cybernetics & Control Theory
↗ Complex System Science & Systems Theory
↗ Management Science ↗ Multi-Criteria Decision Making (MCDM) & Analysis (MCDA)
Operations research (British English: operational research), 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 (or short for MS) 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 concern problems in a variety of industries.
Operations research (OR) encompasses the development and the use of a wide range of problem-solving techniques and methods applied in the pursuit of improved decision-making and efficiency, such as simulation, mathematical optimization, queueing theory and other stochastic-process models, Markov decision processes, econometric methods, data envelopment analysis, ordinal priority approach, neural networks, expert systems, decision analysis, and the analytic hierarchy process.[4] Nearly all of these techniques involve the construction of mathematical models that attempt to describe the system. Because of the computational and statistical nature of most of these fields, OR also has strong ties to computer science and analytics. Operational researchers faced with a new problem must determine which of these techniques are most appropriate given the nature of the system, the goals for improvement, and constraints on time and computing power, or develop a new technique specific to the problem at hand (and, afterwards, to that type of problem).
🔗 https://en.wikipedia.org/wiki/Operations_research#Problems_addressed
- critical path analysis or project planning: identifying those processes in a multiple-dependancy project which affect the overall duration of the project
- Floorplanning: designing the layout of equipment in a factory or components on a computer chip to reduce manufacturing time (therefore reducing cost)
- Network optimization: for instance, setup of telecommunications or power system networks to maintain quality of service during outages
- Resource allocation problems
- Facility location
- Assignment Problems:
- Optimal search
- Routing, such as determining the routes of buses so that as few buses are needed as possible
- Supply chain management: managing the flow of raw materials and products based on uncertain demand for the finished products
- Project production activities: managing the flow of work activities in a capital project in response to system variability through operations research tools for variability reduction and buffer allocation using a combination of allocation of capacity, inventory and time
- Efficient messaging and customer response tactics
- Automation: automating or integrating robotic systems in human-driven operations processes
- Globalization: globalizing operations processes in order to take advantage of cheaper materials, labor, land or other productivity inputs
- Transportation: managing freight transportation and delivery systems (Examples: LTL shipping, intermodal freight transport, travelling salesman problem, driver scheduling problem)
- Scheduling:
- Personnel staffing
- Manufacturing steps
- Project tasks
- Network data traffic: these are known as queueing models or queueing systems.
- Sports events and their television coverage
- Blending of raw materials in oil refineries
- Determining optimal prices, in many retail and B2B settings, within the disciplines of pricing science
- Cutting stock problem: Cutting small items out of bigger ones.
Operational research is also used extensively in government where evidence-based policy is used.
🔗 https://en.wikipedia.org/wiki/Operations_research#Related_fields
Some of the fields that have considerable overlap with Operations Research and Management Science include:
- Business analytics
- Computer science
- Data mining/Data science/Big data
- Decision analysis
- Decision intelligence
- Engineering
- Financial engineering
- Forecasting
- Game theory
- Geography/Geographic information science
- Graph theory
- Industrial engineering
- Inventory Control
- Logistics
- Mathematical modeling
- Mathematical optimization
- Probability and statistics
- Project management
- Policy analysis
- Queuing Theory
- Simulation
- Social network/Transportation forecasting models
- Stochastic processes
- Supply chain management
- Systems engineering