scholarly journals Solving k-obnoxious facility location problem on a plane

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Utpal Kumar Bhattacharya

 In this paper k-obnoxious facility location problem has been modeled as a pure planner location problem.  Area restriction concept has been incorporated by inducting a convex polygon in the constraints set. A linear programming iterative algorithm for k- obnoxious facility locations has been developed. An upper bound has been incorporated in the algorithm to get the  optimal solution. Also the concept of upper bound has reduced  the number of linear programming problems to solved in the algorithm. Rectilinear distance norm has been considered as the distance measure as it is more appropriate to the various realistic situations. 

2000 ◽  
Vol 10 (06) ◽  
pp. 581-592 ◽  
Author(s):  
BOAZ BEN-MOSHE ◽  
MATTHEW J. KATZ ◽  
MICHAEL SEGAL

We present efficient algorithms for several instances of the following facility location problem. Place k obnoxious facilities, with respect to n given demand sites and m given regions, where the goal is to maximize the minimal distance between a demand site and a facility, under the constraint that each of the regions must contain at least one facility. We also present an efficient solution to the following planar problem that arises as a subproblem. Given n transmitters, each of range r, construct a compact data structure that supports coverage queries, i.e., determine whether a query polygonal/rectangular region is fully covered by the transmitters.


1996 ◽  
Vol 12 (1) ◽  
pp. 105-110 ◽  
Author(s):  
E. Brown ◽  
Y. Fathi ◽  
R. Sowell

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 118 ◽  
Author(s):  
Jared Lynskey ◽  
Kyi Thar ◽  
Thant Oo ◽  
Choong Hong

Currently, industry and academia are undergoing an evolution in developing the next generation of drone applications. Including the development of autonomous drones that can carry out tasks without the assistance of a human operator. In spite of this, there are still problems left unanswered related to the placement of drone take-off, landing and charging areas. Future policies by governments and aviation agencies are inevitably going to restrict the operational area where drones can take-off and land. Hence, there is a need to develop a system to manage landing and take-off areas for drones. Additionally, we proposed this approach due to the lack of justification for the initial location of drones in current research. Therefore, to provide a foundation for future research, we give a justified reason that allows predetermined location of drones with the use of drone ports. Furthermore, we propose an algorithm to optimally place these drone ports to minimize the average distance drones must travel based on a set of potential drone port locations and tasks generated in a given area. Our approach is derived from the Facility Location problem which produces an efficient near optimal solution to place drone ports that reduces the overall drone energy consumption. Secondly, we apply various traveling salesman algorithms to determine the shortest route the drone must travel to visit all the tasks.


2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Ľuboš Buzna ◽  
Michal Koháni ◽  
Jaroslav Janáček

We present a new approximation algorithm to the discrete facility location problem providing solutions that are close to the lexicographic minimax optimum. The lexicographic minimax optimum is a concept that allows to find equitable location of facilities serving a large number of customers. The algorithm is independent of general purpose solvers and instead uses algorithms originally designed to solve thep-median problem. By numerical experiments, we demonstrate that our algorithm allows increasing the size of solvable problems and provides high-quality solutions. The algorithm found an optimal solution for all tested instances where we could compare the results with the exact algorithm.


2014 ◽  
Vol 40 (4) ◽  
pp. 27-36
Author(s):  
N. Dedović ◽  
Snežana Matić-Kekić ◽  
M. Tomić ◽  
L. Savin ◽  
M. Simikić

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