A Reinforced Evolution-Based Approach to Multi-Resource Load Balancing

This is the accepted version of the paper published in Journal of Theoretical & Applied Information Technology Vol 4 No 8 (2008) . ABSTRACT This paper presents a reinforced genetic approach to a defined d - resource system optimization problem . The classical evolution schema was ineffective due to a very strict feasibility function in the studied problem. Hence, the presented strategy has introduced several modifications and adaptations to standard genetic routines, e.g.: a migration operator which is an analogy to the biological random genetic drift. INTRODUCTION A funda mental goal in computer science is to provide an algorithm which would determine an optimal solution in acceptable time. Computational Complexity Theory is the field which studies the efficiency of computation; its major goals are to find efficient algorit hms for natural problems or to show that no efficient solutions exist. NP - hard (Nondeterministic Polynomial - time hard), represents a class of problems which are'at least as difficult as problems in NP' [7] [19] . NP - complete problems can be solve d by means of exhaustive search.