论文信息 - Non-dominated sorting environmental adaptation method (NS-EAM)

Non-dominated sorting environmental adaptation method (NS-EAM)

A modified version of NSGA-II named as NSEAM is proposed to solve multi-objective optimization (MOO) problems, which is better in performance as compared to NSGA-II. In this proposed algorithm a new Bio inspired algorithm (EAM) is used instead of genetic algorithm. Benchmark functions have been used to justify the performance of this newly proposed algorithm. Initially this bio inspired algorithm was created for the purpose of solving single objective optimization (SOO) problems and it had already showed promising results as compared to the currently prevailing evolutionary algorithms. So it was thought to extend this EAM algorithm's application area over MOO problems. With slight change in the present SOO algorithm, it can be applied in the MOO problems. This proposed algorithm is compared with NSGA-II and Result analysis shows that it is more efficient and converges to the true parito-optimal front very rapidly.

[1] Kalyanmoy Deb,et al. A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[2] Oliver Kramer,et al. Evolutionary self-adaptation: a survey of operators and strategy parameters , 2010, Evol. Intell..

[3] C. Fonseca,et al. GENETIC ALGORITHMS FOR MULTI-OBJECTIVE OPTIMIZATION: FORMULATION, DISCUSSION, AND GENERALIZATION , 1993 .

[4] Peter J. Fleming,et al. An Overview of Evolutionary Algorithms in Multiobjective Optimization , 1995, Evolutionary Computation.

[5] Aravind Seshadri,et al. A FAST ELITIST MULTIOBJECTIVE GENETIC ALGORITHM: NSGA-II , 2000 .

[6] Shailesh Tiwari,et al. A bio inspired algorithm for solving optimization problems , 2011, 2011 2nd International Conference on Computer and Communication Technology (ICCCT-2011).