Evolutionary design of combinational digital circuits: State of the art, main problems, and future trends

Abstract

In this paper a state of the art, main problems and future trends concerning evolutionary design of combinational digital circuits are presented. Several evolutionary algorithms for design and optimization of combinational digital circuits are also shortly described. In evolutionary design methods the main problem is related to "combinatorial explosion" existing in those methods. Because evolutionary design methods are based on "generate and test" model, therefore together with growing of digital circuit input number, the number of potential combinations which must be tested are growing exponentially. This problem is a "bottle-neck" of those methods, and therefore it is discussed in details in this paper. To solve this problem it becomes important to elaborate efficient decomposition techniques of the designed circuits to some less complex sub-circuits, and then to design each of them independently. Also, it is important to create novel genetic operators (as mutation and crossover) which will always lead to acceptable solutions (solutions which satisfy the truth table). Due to such kind of operators, any repair mechanisms need not necessarily be used, and therefore the "generate and test" model will be simplified only to generation of new solutions, and therefore evolutionary design methods will become more effective.