**Operations Research (OR)**

Operations research, or operational research in British usage, is a discipline that deals with the application of advanced analytical methods to help make better decisions. It is often considered to be a sub-field of mathematics. The terms management science and decision science are sometimes used as synonyms. Employing techniques from other mathematical sciences, such as mathematical modeling, statistical analysis, and mathematical optimization, operations research arrives at optimal or near-optimal solutions to complex decision-making problems. Because of its emphasis on human-technology interaction and because of its focus on practical applications, operations research has overlap with other disciplines, notably industrial engineering and operations management, and draws on psychology and organization science. Operations research is often concerned with determining the maximum (of profit, performance, or yield) or minimum (of loss, risk, or cost) of some real-world objective. Originating in military efforts before World War II, its techniques have grown to concern problems in a variety of industries. … **Trellis Graphics**

Extremely useful approach for graphical exploratory data analysis (EDA). Allows to examine for complicated, multiple variable relationships. Types of plots:

• xyplot: scatterplot

• bwplot: boxplots

• stripplot: display univariate data against a numerical variable

• dotplot: similar to stripplot

• histogram

• densityplot: kernel density estimates

• barchart

• piechart: (Not available in R)

• splom: scatterplot matrices

• contourplot: contour plot of a surface on a regular grid

• levelplot: pseudo-colour plot of a surface on a rectangular grid

• wireframe: perspective plot of a surface evaluated on a regular grid

• cloud: perspective plot of a cloud of points (3D scatterplot)

https://…/chapter4.pdf … **Simulated Annealing (SA)**

Simulated annealing (SA) is a generic probabilistic metaheuristic for the global optimization problem of locating a good approximation to the global optimum of a given function in a large search space. It is often used when the search space is discrete (e.g., all tours that visit a given set of cities). For certain problems, simulated annealing may be more efficient than exhaustive enumeration – provided that the goal is merely to find an acceptably good solution in a fixed amount of time, rather than the best possible solution. …

# If you did not already know

**27**
*Thursday*
Jul 2017

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