.png){kind=icon}
.png){kind=icon}
Return
Exact Biobjective Optimization Methods for Camera Coverage Problem in Three-Dimensional Areas
.png){kind=icon}
PRE
AI
DOI：10.1109/JSEN.2016.2519451.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper deals with the problem of deploying necessary camera sensors ensuring the maximum sum of weighted target points in 3-D areas while minimizing the total sensor network camera cost. The problem is NP-complete as it can be considered as a total grid coverage problem, which is an NP-complete problem when the sensing field is a 2-D area. We solve the problem optimally by three exact biobjective methods: 1) weighted sum scalarization approach; 2) a two-phase method; and 3) an epsilon-constraint method. The simulation results show that each adopted resolution approach dominates the other approaches in at least one criterium when the problem size increases and the resolution process is stopped after a predefined computation time limit.
Keywords:
Coverage problem
sensor camera deployment
exact bi-objective optimization methods
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.5
Papers:
2.1W
Citations:
7.3W