Practical results of artificial immune Systems for combinatorial optimization problems

Abstract

Artificial immune systems (AIS) represent a family of bio-inspired populational meta-heuristic algorithms successful in solving complex problems. Combinatorial optimization problems constitute a class of problems with a discrete set of solutions. In this study we provide an initial evaluation of the practical results of AIS for two well known combinatorial optimization problems - the linear ordering problem and independent task scheduling.