Decomposition-based Evolutionary Multi- Objective Optimization Approach to the De- Sign of Concentric Circular Antenna Ar- Rays
نویسندگان
چکیده
We investigate the design of Concentric Circular Antenna Arrays (CCAAs) with λ/2 uniform inter-element spacing, non-uniform radial separation, and non-uniform excitation across different rings, from the perspective of Multi-objective Optimization (MO). Unlike the existing single-objective design approaches that try to minimize a weighted sum of the design objectives like Side Lobe Level (SLL) and principal lobe Beam-Width (BW), we treat these two objectives individually and use Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D) with Differential Evolution (DE), called MOEA/D-DE, to achieve the best tradeoff between the two objectives. Unlike the single-objective approaches, the MO approach provides greater flexibility in the design by yielding a set of equivalent final (nondominated) solutions, from which the user can choose one that attains a suitable trade-off margin as per requirements. We illustrate that the best compromise solution attained by MOEA/D-DE can comfortably outperform state-of-the-art variants of single-objective algorithms like Particle Swarm Optimization (PSO) and Differential Evolution. In addition, we compared the results obtained by MOEA/D-DE with those obtained by one of the most widely used MO algorithm called NSGA-2 and a multi-objective DE variant, on the basis of the Rindicator, hypervolume indicator, and quality of the best tradeoff solutions obtained. Our simulation results clearly indicate the superiority of the design based on MOEA/D-DE. Received 7 March 2013, Accepted 31 May 2013, Scheduled 4 June 2013 * Corresponding author: Swagatam Das ([email protected]).
منابع مشابه
Multi-objective optimization design of plate-fin heat sinks using an Evolutionary Algorithm Based On Decomposition
This article has no abstract.
متن کاملA MULTI-OBJECTIVE EVOLUTIONARY ALGORITHM USING DECOMPOSITION (MOEA/D) AND ITS APPLICATION IN MULTIPURPOSE MULTI-RESERVOIR OPERATIONS
This paper presents a Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) for the optimal operation of a complex multipurpose and multi-reservoir system. Firstly, MOEA/D decomposes a multi-objective optimization problem into a number of scalar optimization sub-problems and optimizes them simultaneously. It uses information of its several neighboring sub-problems for optimizin...
متن کاملA Multi-objective Memetic Optimization Ap- Proach to the Circular Antenna Array De- Sign Problem
The paper provides a novel approach to the design of nonuniform planar circular antenna arrays for achieving maximal side lobe level suppression and directivity. The current excitation amplitudes and phase perturbations of the array elements are determined using an Adaptive Memetic algorithm resulting from a synergy of Differential Evolution (DE) and Learning Automata that is able to significan...
متن کاملApproximate Pareto Optimal Solutions of Multi objective Optimal Control Problems by Evolutionary Algorithms
In this paper an approach based on evolutionary algorithms to find Pareto optimal pair of state and control for multi-objective optimal control problems (MOOCP)'s is introduced. In this approach, first a discretized form of the time-control space is considered and then, a piecewise linear control and a piecewise linear trajectory are obtained from the discretized time-control space using ...
متن کاملA Hybrid MOEA/D-TS for Solving Multi-Objective Problems
In many real-world applications, various optimization problems with conflicting objectives are very common. In this paper we employ Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), a newly developed method, beside Tabu Search (TS) accompaniment to achieve a new manner for solving multi-objective optimization problems (MOPs) with two or three conflicting objectives. This i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013