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Multi Expression Programming (MEP) is an evolutionary algorithm for generating mathematical functions describing a given set of data. MEP is a Genetic Programming variant encoding multiple solutions in the same chromosome. MEP representation is not specific (multiple representations have been tested). In the simplest variant, MEP chromosomes are linear strings of instructions. This representation was inspired by Three-address code. MEP strength consists in the ability to encode multiple solutions, of a problem, in the same chromosome. In this way, one can explore larger zones of the search space. For most of the problems this advantage comes with no running-time penalty compared with genetic programming variants encoding a single solution in a chromosome.^[1]^[2]^[3]

^ Oltean M.; Dumitrescu D.: "Multi Expression Programming", Technical report, Univ. Babes-Bolyai, Cluj-Napoca, 2002
^ Oltean M.; Grosan C.: "Evolving Evolutionary Algorithms using Multi Expression Programming", The 7th European Conference on Artificial Life, September 14–17, 2003, Dortmund, Edited by W. Banzhaf (et al), LNAI 2801, pp. 651-658, Springer-Verlag, Berlin, 2003
^ Oltean M.; Grosan C.: "Evolving Digital Circuits using Multi Expression Programming", NASA/DoD Conference on Evolvable Hardware, 24–26 June, Seattle, Edited by R. Zebulum (et al.), pages 87-90, IEEE Press, NJ, 2004