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  2. Operations research - Wikipedia

    en.wikipedia.org/wiki/Operations_research

    The field of management science (MS) is known as using operations research models in business. [34] Stafford Beer characterized this in 1967. [ 35 ] Like operational research itself, management science is an interdisciplinary branch of applied mathematics devoted to optimal decision planning, with strong links with economics, business ...

  3. Mathematical optimization - Wikipedia

    en.wikipedia.org/wiki/Mathematical_optimization

    Space mapping is a concept for modeling and optimization of an engineering system to high-fidelity (fine) model accuracy exploiting a suitable physically meaningful coarse or surrogate model. In a number of subfields, the techniques are designed primarily for optimization in dynamic contexts (that is, decision making over time):

  4. Business analytics - Wikipedia

    en.wikipedia.org/wiki/Business_analytics

    Business analytics (BA) refers to the skills, technologies, and practices for iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods .

  5. Business process modeling - Wikipedia

    en.wikipedia.org/wiki/Business_process_modeling

    A business process modeling of a process with a normal flow with the Business Process Model and Notation. Business process modeling (BPM) is the action of capturing and representing processes of an enterprise (i.e. modeling them), so that the current business processes may be analyzed, applied securely and consistently, improved, and automated.

  6. Simulation-based optimization - Wikipedia

    en.wikipedia.org/wiki/Simulation-based_optimization

    Simulation-based optimization (also known as simply simulation optimization) integrates optimization techniques into simulation modeling and analysis. Because of the complexity of the simulation, the objective function may become difficult and expensive to evaluate. Usually, the underlying simulation model is stochastic, so that the objective ...

  7. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision-making for candidate transactions.

  8. Price optimization - Wikipedia

    en.wikipedia.org/wiki/Price_optimization

    Price optimization utilizes data analysis to predict the behavior of potential buyers to different prices of a product or service. Depending on the type of methodology being implemented, the analysis may leverage survey data (e.g. such as in a conjoint pricing analysis [7]) or raw data (e.g. such as in a behavioral analysis leveraging 'big data' [8] [9]).

  9. Supply chain optimization - Wikipedia

    en.wikipedia.org/wiki/Supply_chain_optimization

    Typically, supply-chain managers aim to maximize the profitable operation of their manufacturing and distribution supply chain. This could include measures like maximizing gross margin return on inventory invested (balancing the cost of inventory at all points in the supply chain with availability to the customer), minimizing total operating expenses (transportation, inventory and ...