Solving curve fitting problems using genetic programming

Genetic programming is a branch of genetic algorithms. The main difference between genetic programming and genetic algorithms is the representation of the solution. Genetic programming creates computer programs in LISP computer language as the solution whereas genetic algorithms create a string of numbers that represent the solution (see Holland, J.H., 1975). The new way of representation used in GP encouraged researchers to use it in solving design problems where the size and shape of the solution is unknown (see Koza, J.R., 1992). Curve fitting problems used to be solved by assuming the equation shape or degree then searching for the parameter values as done in regression techniques. This paper demonstrates that curve fitting problems can be solved using GP without need to assume the equation shape. An object oriented technique has been used to design and implement a general purpose GP engine.