A quantum-inspired genetic algorithm for solving the antenna positioning problem

摘要: Abstract Cellular phone networks are one of today's most popular means communication. The big popularity and accessibility the services proposed by these have made mobile industry a field with high standard competition where service quality is key. Actually, such strongly bound to design themselves, optimisation issues exist at each step. Thus, any process that cannot cope problems may alter phase ultimately provided. Antenna Positioning Problem (APP) determinant engineers face during network life cycle. This paper proposes new variant Quantum-Inspired Genetic Algorithm (QIGA) based on novel quantum gate for solving APP. In order assess scalability, efficiency robustness algorithm, experiments been carried out realistic, synthetic random benchmarks different dimensions. Several statistical analysis tests as well. State-of-the-art algorithms designed solve APP, Population-Based Incremental Learning (PBIL) (GA), taken comparison basis. Performance evaluation approach proves it efficient, robust scalable; could outperform both PBIL GA in many benchmark instances.