Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 780637, 14 pages
Research Article

Goal-Programming-Driven Genetic Algorithm Model for Wireless Access Point Deployment Optimization

1Graduate Institute of Information and Logistics Management, National Taipei University of Technology, Taipei 10608, Taiwan
2Department of Information Management, Chang Gung University, Tao Yuan 333, Taiwan

Received 24 February 2012; Accepted 8 May 2012

Academic Editor: Jung-Fa Tsai

Copyright © 2012 Chen-Shu Wang and Ching-Ter Chang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Appropriate wireless access point deployment (APD) is essential for ensuring seamless user communication. Optimal APD enables good telecommunication quality, balanced capacity loading, and optimal deployment costs. APD is a typical NP-complex problem because improving wireless networking infrastructure has multiple objectives (MOs). This paper proposes a method that integrates a goal-programming-driven model (PM) and a genetic algorithm (GA) to resolve the MO-APD problem. The PM identifies the target deployment subject of four constraints: budget, coverage, capacity, and interference. The PM also calculates dynamic capacity requirements to replicate real wireless communication. Three experiments validate the feasibility of the PM. The results demonstrate the utility and stability of the proposed method. Decision makers can easily refer to the PM-identified target deployment before allocating APs.