Session:

LBP - Late Breaking Papers

Title:

An Evolutionary Approach for Multiobjective Optimization using Adaptive Representation of Solutions

Authors:

Crina Grosan

Abstract:

Many algorithms for multiobjective optimization have been proposed in the last years. In the recent past a great importance have the MOEAs able to solve problems with more than two objectives and with a large number of decision vectors (space dimensions). The difficulties occur when problems with more than three objectives (higher dimensional problems) are considered. In this paper, a new algorithm for multiobjective optimization called Multiobjective Adaptive Representation Evolutionary Algorithm (MAREA) is proposed. MAREA combines an evolution strategy and an steady-state algorithm. The performance of the MAREA algorithm is assessed by using several well-known test functions having more than two objectives. MAREA is compared with the best present day algorithms: SPEA2, PESA and NSGA II. Results show that MAREA has a very good convergence.