Linear Array Synthesis Using Biogeography Based Optimization

Abstract

Abstract-This paper presents a novel optimization technique biogeography based optimization (BBO) for antenna array synthesis. BBO is a relatively new evolutionary global optimization technique based on the science of biogeography. It is capable of solving linear and non-linear problems. In this paper, BBO algorithm is used to determine an optimum set of amplitudes of antenna elements that provide a radiation pattern with maximum side lobe level reduction and/or null placement in the specified directions. The results obtained show the effectiveness of the BBO algorithm, and they are better than previous published results.

Pattern Nulling of Linear Antenna Arrays Using Backtracking Search Optimization Algorithm

“…Additionally, the metaheuristic algorithms are capable of escaping from local minima. Genetic algorithm (GA) [7-12, 20, 23, 25, 39], tabu search algorithm (TSA) [23,30], modified touring ant colony algorithm (MTACO) [13], particle swarm optimization (PSO) [15,30,33], bees algorithm (BA) [16,29], bacterial foraging algorithm (BFA) [19,24], clonal selection algorithm (CLONALG) [21], plant growth simulation algorithm (PGSA) [26], differential evolution (DE) algorithm [14,18,27], biogeography based optimization (BBO) [28], multiobjective DE (MODE) [30], memetic algorithm (MA) [17,23,30], nondominated sorting GA-2 (NSGA-2) [30], decomposition with DE (MOEA/D-DE) [30], comprehensive learning PSO (CLPSO) [31], seeker optimization algorithm (SOA) [32], invasive weed optimization (IWO) algorithm [34], harmony search algorithm (HSA) [35], firefly algorithm (FA) [36,38], cuckoo search (CS) algorithm [37,42], differential search algorithm (DSA) [40], cat swarm optimization (CSO) [41], and mean variance mapping optimization (MVMO) [43] can be given as the examples of these metaheuristic algorithms used for pattern nulling.…”

A Novel Hybrid IWO/WDO Algorithm for Interference Minimization of Uniformly Excited Linear Sparse Array by Position-Only Control

“…The optimized positions of array elements are mentioned in Table VI. The hybrid algorithm achieves minimum SLL of -19.70 dB compared to -15.7 dB, -17.11 dB, -18.80 dB and -16.93 dB in IWO, WDO, PSO [2] and BBO [6] respectively and the NDL at 99º is -108.60 dB, mentioned in Table VII. In this case, a better null control is obtained at 99º and the SLL is better than other algorithms reported in Table VII, but slightly less than the CLPSO and DE.…”

“…Three examples of pattern synthesis are considered to illustrate the efficacy of hybrid algorithm. The results are compared with those obtained by IWO and other algorithm reported in [2]- [4], [6]. A other six algorithms in terms of null control, minimum SLL, beam width control and the rate of convergence.…”

“…Since 1970's various evolutionary algorithms have emerged such as genetic algorithm (GA), Particle Swarm Optimization (PSO) [2], Comprehensive Learning Particle Swarm Optimization (CLPSO) [3], Differential Evolution (DE) [4], Bacterial Foraging Optimization (BFO) [5], Biogeography Based Optimization (BBO) [6], Invasive Weed Optimization [7], [13]- [14], Wind Driven Optimization (WDO) [8] and many others. They have been successfully implemented for solving multi-dimensional and multimodal problems such as the array synthesis [1]- [14].…”

Design of Linear and Circular Antenna Arrays Using Cuckoo Optimization Algorithm

“…There are a number of different nature inspired methods that have been used for antenna array synthesis. Among them are genetic algorithms (GA) [1,2], differential evolution (DE) [2][3][4], ant colony optimization (ACO) [5,6], particle swarm optimization (PSO) [7][8][9][10][11][12][13][14][15][16], modified invasive weed optimization (MIWO) [17], firefly algorithm (FA) [18][19][20], biogeography based optimization (BBO) [21][22][23][24] and cuckoo search (CS) [25]. These methods perform better and provide more flexible results than the classical methods for antenna array synthesis.…”