Optimal Placement of Weather Radars Network as a Multi-objectives Problem
Redouane Boudjemaa ()
Additional contact information
Redouane Boudjemaa: University M’Hamed Bougara of Boumerdes
A chapter in Operations Research Proceedings 2016, 2018, pp 71-76 from Springer
Abstract:
Abstract This work proposes an approach to the optimal placement of a weather radar network based on solutions to a multi-objective optimization problem. Given a finite number of weather radars, a network is produced by taking into account the maximization of network coverage area and the minimization of network general cost. Several constraints on the solutions are considered such as terrain blockage, radar beam elevation and distance from power grid and roads. By transforming the search space into a gridded system, a reduction in the number of possible combinations of radar networks is achieved making the problem manageable in size. The multiobjective optimization problem is solved by four different evolutionary algorithms and the obtained results are analysed using different performance metrics. The proposed approach can serve as an analysis tool for a decision support system by providing meteorologists a set of Pareto-optimal solutions to assist in the selection of future prime sites for the installation of weather radars.
Date: 2018
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-319-55702-1_11
Ordering information: This item can be ordered from
http://www.springer.com/9783319557021
DOI: 10.1007/978-3-319-55702-1_11
Access Statistics for this chapter
More chapters in Operations Research Proceedings from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().