Optimizing campus layout with the capacitated P-Median problem
DOI:
https://doi.org/10.14571/brajets.v18.n4.1425-1437Keywords:
p-medians problem, integer linear programming, metaheuristicsAbstract
Many real-world problems involve decision-making. Such scenarios rely on cost or performance measures to assess the quality of solutions and are often modeled as optimization problems. Their solution involves the mathematical formulation of the problem and, in some cases, the adoption of heuristic algorithms. This study presents a case study that applies mathematical programming and the iterated greedy metaheuristic to solve a urban planning problem in a university campus. To this end, the scenario was modeled as the capacitated p-median problem and different instances were generated. The results indicate that the exact approach is capable of solving small instances, while the iterated greedy provides good solutions for larger instances. Moreover, the metaheuristic produces high-quality solutions in less time than the exact method, demonstrating its feasibility for real-world urban planning scenarios.
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