A heuristic non-dominated sorting genetic algorithm-II for satellite-module layout optimisation

Authors:
Y. Xu;C. Li;Y. J. Shi;H. F. Teng
Affiliations:
Department of Computer Science and Engineering, Dalian University of Technology, 116024 Dalian, China.;Department of Mechanical Engineering, Dalian University of Technology, 116024 Dalian, China.;Department of Mechanical Engineering, Dalian University of Technology, 116024 Dalian, China.;Department of Mechanical Engineering, Dalian University of Technology, 116024 Dalian, China
Venue:
International Journal of Computer Applications in Technology
Year:
2010

Citing 8
Cited 3

Multiobjective optimization with messy genetic algorithms

SAC '00 Proceedings of the 2000 ACM symposium on Applied computing - Volume 1
The irregular cutting-stock problem mdash; a new procedure for deriving the no-fit polygon

Computers and Operations Research
Layout optimization for the objects located within a rotating vessel — a three-dimensional packing problem with behavioral constraints

Computers and Operations Research
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization

Proceedings of the 5th International Conference on Genetic Algorithms
Adaptive-growth-type 3D representation for configuration design

Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy

Evolutionary Computation
Layout optimization of satellite module using soft computing techniques

Applied Soft Computing
A fast and elitist multiobjective genetic algorithm: NSGA-II

IEEE Transactions on Evolutionary Computation

An evolutionary linear programming algorithm for solving the stock reduction problem

International Journal of Computer Applications in Technology
Task allocation in distributed computing systems using adaptive particle swarm optimisation

International Journal of Computer Applications in Technology
Simulation-based ATPG for low power testing of crosstalk delay faults in asynchronous circuits

International Journal of Computer Applications in Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes a Heuristic Non-dominated Sorting Genetic Algorithm-II (HNSGA-II) to solve alayout optimisation problem such as that of satellite-modules. Firstly, we apply a diversity degree method to evaluate the dominance (or inferiority) of solutions in the same front instead of the crowding-distance method. Secondly, a filter technique of a Pareto solution set is introduced to preserve the elite individuals more effectively. Thirdly, three kinds of operators are adopted to improve search performance. Finally, we give two heuristic layout strategies in the optimisation process. The numerical experiments of a simplified satellite-module layout design show the feasibility and the effectiveness of the proposed algorithm.