Memetic algorithms provide one of the most effective and flexible metaheuristic approaches for tackling hard optimization problems. Memetic algorithms address the difficulty of developing high-performance universal heuristics by encouraging the exploitation of multiple heuristics acting in concert, making use of all available sources of information for a problem. This approach has resulted in a rich arsenal of heuristic algorithms and metaheuristic frameworks for many problems. This chapter discusses the philosophy of the memetic paradigm, lays out the structure of a memetic algorithm, develops several example algorithms, surveys recent work in the field, and discusses the possible future directions of memetic algorithms.
CITATION STYLE
Moscato, P., Cotta, C., & Mendes, A. (2004). Memetic Algorithms (pp. 53–85). https://doi.org/10.1007/978-3-540-39930-8_3
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