A Comparison of Evolutionary Programming and Genetic Algorithms for Electronic Part Placement

Evolutionary programming (EP) is a robust optimization technique which can be applied to complex multidimensional problems that are difficult for traditional optimization methods. This paper considers the use of EP to minimize the manufacturing effort of printed circuit boards (PCB) with respect to electronic part placement. The results are compared with those presented in a recent paper examining the same problem using genetic algorithms (GAs). Three industrial standard PCB fabrication assembly methods are abstracted as a combinatorial optimization problem: the traveling salesman problem (TSP). It is shown that EP can yield solutions that are comparable to those found using GAs, but with fewer operators.