# Continuous Space Wireless Communication Tower Placement by Hybrid Simulated Annealing
###### Abstract  
Wireless communication tower placement arises in many real-world applications. This paper investigates a new emerging wireless communication tower placement problem, namely, _continuous space wireless communication tower placement_. Unlike existing wireless communication tower placement problems, which are discrete computational problems, this new wireless communication tower placement problem is a continuous space computational problem. In this paper, we formulate the new wireless communication tower placement problem and propose a hybrid simulated annealing algorithm that can take advantage of the powerful exploration capacity of simulated annealing and the strong exploitation capacity of a local optimization procedure. We also demonstrate through experiments the effectiveness of this hybridization technique and the good performance and scalability of the hybrid simulated annulling in this paper.  
communication tower placement; optimization algorithm; simulated annealing: hybrid intelligent algorithm +
Footnote †: journal:  
0000-0001-4600-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-00000-00000-0000-00000-00000-0  
Instead, in today's wireless communication tower placement, we need to determine where the wireless communication towers should be placed in a geographical area, which is a continuous space.  
There are two types of wireless communication tower placement problems. One wireless communication tower placement problem is to find a placement of the minimal number of wireless communication towers covering a given geographical area. Another is to find a placement of a fixed number of wireless communication towers that cover the maximal number of users of the wireless communication network. Both of the wireless communication tower placement options are continuous space optimization problems as their search spaces for an optimal solution are both in a continuous space. This paper concentrates on the latter problem of placement of wireless communication towers.  
In this paper, the new continuous space communication tower placement problem is formulated as a continuous function optimization problem, and a hybrid simulated annealing (SA) is proposed, which capitalizes on the powerful exploration capability of SA and the effective exploitation capability of a local search algorithm. In this paper, we also prove the effectiveness of the hybridization technique and evaluate the performance and scalability of the hybrid SA.  
SA is an optimization algorithm that can be applied to a wide range of problems. Like other metaheuristic algorithms, it is particularly suitable for solving problems where traditional optimization methods may get stuck in local optima or struggle with complex, multimodal, or nonconvex solution spaces. The main reason why we chose SA is that the new continuous space communication tower placement problem is a continuous optimization problem and SA is versatile in handling continuous variable optimization problems. Furthermore, SA is not a population-based metaheuristic algorithm. Therefore, it is computationally cheaper than those population-based metaheuristic algorithms.  
The remainder of the paper is organized as follows. Section 2 discusses related work. Section 3 formulates the new continuous space wireless communication power placement problem. Section 4 presents our hybrid SA algorithm for the continuous space wireless communication tower placement problem. The effectiveness of hybridization and the performance and scalability of the hybrid SA are studied through experiments in Section 5. Finally, we discuss and conclude the research in Section 6.