In this paper a new evolutionary paradigm, called Multi-Expression Programming (MEP), intended for solving computationally difficult problems is proposed. A new encoding method is designed. MEP individuals are linear entities that encode complex computer programs. In this paper MEP is used for solving some computationally difficult problems like symbolic regression, game strategy discovering, and for generating heuristics. Other exciting applications of MEP are suggested. Some of them are currently under development. MEP is compared with Gene Expression Programming (GEP) by using a well-known test problem. For the considered problems MEP performs better than GEP.
Evolving TSP heuristics using Multi Expression Programming
Multi Expression Programming (MEP) google