Evolutionary Approaches to Linear Ordering Problem

Linear ordering problem (LOP) is a well know optimization problem attractive for its complexity (it is a NP hard problem), rich collection of testing data and variety of real world applications. In this paper, we investigate the usage and performance of two variants of genetic algorithms - mutation only genetic algorithms and higher level chromosome genetic algorithms - on the linear ordering problem. Both methods are tested and evaluated on a collection of real world and artificial LOP instances.