混合式進化演算法於無線基地台配置決策之應用

Hybrid Evolutionary Approach for the Cellular Phone Stations Allocation Problems

黃格威(Ke-Wei Huang)

國立虎尾科技大學/管理學院/工業工程與管理研究所/碩士(2006年)

摘要

由於行動通訊快速的發展下帶動國內行動電話持有人口，行動電話的使用普及連帶也使得基地台數成長迅速，不當的設置基地台不僅對於業者設置成本造成浪費也並無法達到較佳的通訊品質，故通訊業者目前所面臨這些問題的窘境下，如何在通訊服務品質與基地台較佳設置之間取得一個平衡點是通訊業者即須解決的問題，有鑑於此，如何在有限的預算決策下，進行最佳的無線基地台設置，並提供民眾較佳的服務品質，就成為一個相當重要的議題。在本研究中提出混合式進化演算法(IAPSO)，以免疫演算法與粒子群最佳化二種進化演算法作結合，來決解有資源限制下多類別的無線基地台配問題，由實驗數據結果得知，本研究所提出的方法在解決資源限制下無線基地台配置的決策問題，顯示該法之優異性與穩定性。藉由本研究的研究結果可以提供通訊業者在配置無線基地台時選擇較佳的決策方案。

並列摘要

As the rapid development of mobile technologies, it causes cellular phone users increasing tremendously. The signal transmission stations are widely built because the population of cellular phones user is increased hugely. Incorrect setup of stations is not only causing the unnecessary cost but also making the poor service quality.
How to foster better relations between the setup cost and service quality is very important issue. According to the above difficulties suffered in our study, this thesis is to investigate the nonlinearly constrained cellular phone transmitters locating problems in which the types of transmitters and the corresponding numbers and locations are to be decided simultaneously so as to minimize the maximum communication failure rate that may occurs in a specified area.
In this study, we proposed a hybrid algorithm based on the Immune algorithm and Particle Swarm Optimization (IAPSO). We use the IAPSO to solve the multiple stations location problems. The computational results show that the proposed algorithm can provide the better performance than other approach and/or commercial software. It is wished that our study can provide the Telecommunication Enterprise the optimal/near optimal strategies for the setup of signal transmission stations.

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