January 2020
Intermediate to advanced
346 pages
9h 8m
English
Content preview from Hands-On Genetic Algorithms with Python
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Search problems and combinatorial optimization
One main area of applying genetic algorithms is search problems, which have important applications in fields such as logistics, operations, artificial intelligence, and machine learning. Examples include determining the optimal routes for package delivery, designing hub-based airline networks, managing investment portfolios, and assigning passengers to available drivers in a fleet of taxis.
A search algorithm is focused on solving a problem through methodic evaluation of states and state transitions, aiming to find a path from the initial state to a desirable final (or goal) state. Typically, there is a cost or gain involved in every state transition, and the objective of the corresponding search ...
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