This paper presents a new heuristic algorithm for the following covering problem. For a set of $n$ demand points in continuous space, locate a given number of facilities or sensors anywhere on the plane in order to obtain maximum coverage. This means, in this problem an infinite set of potential locations in continuous space should be explored. We present a heuristic algorithm that finds a near-optimal solution for large-scale instances of this problem in a reasonable time. Moreover, we compare our results with previous algorithms on randomly generated datasets that vary in size and distribution. Our experiments show that in comparison to other methods in the literature, the proposed algorithm is scalable and can find solutions for large-scale instances very fast, when previous algorithms unable to handle these instances. Finally, some results of the tests performed on a real-world dataset are also presented.
Imanparast, M., & Kiani, V. (2021). A practical heuristic for maximum coverage in large-scale continuous location problem. Journal of Mathematical Modeling, 9(4), 555-572. doi: 10.22124/jmm.2021.18624.1594
MLA
Mahdi Imanparast; Vahid Kiani. "A practical heuristic for maximum coverage in large-scale continuous location problem". Journal of Mathematical Modeling, 9, 4, 2021, 555-572. doi: 10.22124/jmm.2021.18624.1594
HARVARD
Imanparast, M., Kiani, V. (2021). 'A practical heuristic for maximum coverage in large-scale continuous location problem', Journal of Mathematical Modeling, 9(4), pp. 555-572. doi: 10.22124/jmm.2021.18624.1594
VANCOUVER
Imanparast, M., Kiani, V. A practical heuristic for maximum coverage in large-scale continuous location problem. Journal of Mathematical Modeling, 2021; 9(4): 555-572. doi: 10.22124/jmm.2021.18624.1594