
The maximal covering location problem (MCLP) is a challenging problem with numerous applications in practice. Previous publications in the area of MCLP proposed models and presented solution methodologies to solve this problem with up to 900 nodes. Due to the fact that in real-life applications, the number of nodes could be much higher, this paper presents a customized Genetic Algorithm (GA) to solve MCLP instances, with up to 2500 nodes. Results show that the proposed approach is capable of solving problems with a fair amount of exactness. In order to fine-tune the algorithm, Tukey’s Least Significant Difference (LSD) tests are employed on a set of test problems.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 55 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
