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Now that we have seen some basic applications of both binary and continuous GAs and discussed some of the fine points of their implementation, it will be fun to look at what can be accomplished with a GA and a bit of imagination. The examples in this chapter make use of some of the advanced topics discussed in Chapter 5 and add variety to the examples presented in Chapter 4. They cover a wide range of areas and include technical as well as nontechnical examples. The first example is the infamous traveling salesperson problem where the GA must order the cities visited by the salesperson.The second example revisits the locating-an-emergency-response unit from Chapter 4 but this time uses a Gray code. Next comes a search for an alphabet that decodes a secret message. The next examples come from engineering design and include robot trajectory planning and introductory stealth design.We end with several examples from science and mathematics that demonstrate some of the ways in which GAs are being used in research: two use data to build inverse models, one couples a simulation with a GA to identify allocations of sources to an air pollution monitor, one combines the GA with another artificial intelligence technique—the neural network—and the final one finds solutions to a nonlinear fifth-order differential equation.