##### DM-47 - Geographic coordinate system

- Distinguish between various latitude definitions (e.g., geocentric, geodetic, astronomic latitudes)
- Explain the angular measurements represented by latitude and longitude coordinates
- Calculate the latitude and longitude coordinates of a given location on the map using the coordinate grid ticks in the collar of a topographic map and the appropriate interpolation formula
- Mathematically express the relationship between Cartesian coordinates and polar coordinates
- Calculate the uncertainty of a ground position defined by latitude and longitude coordinates specified in decimal degrees to a given number of decimal places
- Use GIS software and base data encoded as geographic coordinates to geocode a list of address-referenced locations
- Locate on a globe the positions represented by latitude and longitude coordinates
- Write an algorithm that converts geographic coordinates from decimal degrees (DD) to degrees, minutes, seconds (DMS) format

## AM-78 - Genetic Algorithms and Evolutionary Computing

Genetic algorithms (GAs) are a family of search methods that have been shown to be effective in finding optimal or near-optimal solutions to a wide range of optimization problems. A GA maintains a population of solutions to the problem being solved and uses crossover, mutation, and selection operations to iteratively modify them. As the population evolves across generations, better solutions are created and inferior ones are selectively discarded. GAs usually run for a fixed number of iterations (generations) or until further improvements do not obtain. This contribution discusses the fundamental principles of genetic algorithms and uses Python code to illustrate how GAs can be developed for both numerical and spatial optimization problems. Computational experiments are used to demonstrate the effectiveness of GAs and to illustrate some nuances in GA design.