Optimization of Vehicle-Borne Radar Antenna Pedestal Based on Modified NSGA-II

Abstract:

This paper deals with application of Non-dominated Sorting Genetic Algorithm with elitism (NSGA-II) to solve multi-objective optimization problems of designing a vehicle-borne radar antenna pedestal. Five technical improvements are proposed due to the disadvantages of NSGA-II. They are as follow: (1) presenting a new method to calculate the fitness of individuals in population; (2) renewing the definition of crowding distance; (3) introducing a threshold for choosing elitist; (4) reducing some redundant sorting process; (5) developing a self-adaptive arithmetic cross and mutation probability. The modified algorithm can lead to better population diversity than the original NSGA-II. Simulation results prove rationality and validity of the modified NSGA-II. A uniformly distributed Pareto front can be obtained by using the modified NSGA-II. Finally, a multi-objective problem of designing a vehicle-borne radar antenna pedestal is settled with the modified algorithm.

• Periodical: Advanced Materials Research (Volumes 945-949)
• Pages: 2241-2247
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.945-949.2241
• Online since: June 2014
• Authors: De Gao Zhao*, Qiang Li
• Keywords: Genetic Algorithm (GA), Multi-Objective Optimization (MOP), NSGA-II, Vehicle-Borne Radar Antenna Pedestal

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