Application of Simulated Annealing Algorithm to Optimization Deployment of Mobile Wireless Base Stations

Deployment of mobile wireless base (transceiver) stations (MBTS, vehicles) is expensive, with the wireless provider often offering a basic coverage of BTS in a normal communication data flow. However, during a special festival celebration or a popular outdoor concert in a big city, the quality of the wireless connection would be insufficient. In this situation, the wireless service providers always increase the number of MBTS to improve the density of nets and speed up the data flow of communication. This research intended to construct an integer programming (IP) model to minimize the density gap between wireless request and supply. The solver used was an SA algorithm. In order to validate, the proposed approach was compared to other famous heuristics, such as Random with Tabu and Ransom Search; and it was found that SA outperformed RS by an average of 18%. This result suggested a reduction of the density gap between wireless request and supply by 18% if an MBTS company’s allocation of transceiver stations is optimal, and an SA algorithm is used.