A New Algorithm Using Pareto Archive Evolution Strategy to Multi-Objective Optimization Problem
Many multi-objective optimization algorithms combine with different objectives into one objective using weighting method. In this paper, a novel method named Pareto Archive Evolution Strategy (PAES) which only makes one mutation to create one new solution and use an “archive” which are called Non-Dominated Archive to store the best solution, is introduced. This procedure is completed by a special approach-adaptive grid method, which decides what and which solution are to be archived and where the grid location the solution would be stored. The Pareto front is to be found by this procedure quicker than the classical Multi-objective Genetic Algorithm (MOGA). Simulation results show that the PAES is effective to the multi-objective optimization problems and have the better performance on the time complexity.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
Document Type: Research Article
Publication date: March 1, 2012
More about this publication?
- ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
- Editorial Board
- Information for Authors
- Subscribe to this Title
- Ingenta Connect is not responsible for the content or availability of external websites