Evolutionary algorithms and dynamic programming

Recently, it has been proven that evolutionary algorithms produce good results for a wide range of combinatorial optimization problems. Some of the considered problems are tackled by evolutionary algorithms that use a representation, which enables them to construct solutions in a dynamic programming fashion. We take a general approach and relate the construction of such algorithms to the development of algorithms using dynamic programming techniques. Thereby, we give general guidelines on how to develop evolutionary algorithms that have the additional ability of carrying out dynamic programming steps. Categories and Subject Descriptors F.2.2 [Analysis of Algorithms and Problem Complexity]: Nonnumerical Algorithms and Problems General Terms Algorithms, Design, Performance, Theory Keywords Combinatorial optimization, dynamic programming, evolutionary algorithms

• Type: Conference
• Year: 2009
• Where: GECCO
• Authors: Benjamin Doerr, Anton Eremeev, Christian Horoba, Frank Neumann, Madeleine Theile
• Keywords: Artificial Intelligence, Combinatorial Optimization, Dynamic Programming, Evolutionary Algorithms, GECCO 2009