Evolutionary estimation of assignment-ordering function for CSP-modeled combinatorial optimization

Abstract

A novel evolutionary assignment-ordering approach for combinatorial optimization using constraint satisfaction problem (CSP) modeling is presented. In assignment of values to variables, the order of assignment is determined by an ordering function combined with problem, specific features. No a priory information is available on the assignment-ordering function and it is completely determined by evolutionary optimization to produce the best assignment results. Indeed, experimental evaluations show that the proposed method outperforms very well-known approaches for the solution of NP-hard combinatorial optimization problems.