Models and Heuristic Algorithms for Solving Discrete Location Problems of Temporary Disposal Places in Palembang City

The discrete location problem has given more attention to operations research as the prevalent locationallocation problem in recent years. Discrete location problems have three main classifications: covering-based, median-based, and some different problems. An open facility location must cover demand in terms of range or travelled period in coveringbased problems. The prospective site must cover all request points at the network centre in median-based problems. These problem categories are suitable for determining the public facility's location. There are very few literature reviews and models related to location-allocation theory. This paper aims to present detailed calculations or numerical methods computations and an overview of the studies, types, models, and previous researchers' methods to solve discrete location problems. We describes the set covering location problems, maximal covering location problems, p-center location problems, p-median location problems, and fixed charge facility locations problems. This paper also briefly explains several heuristic algorithms to solve discrete location problems, such as genetic algorithm, particle swamp optimization, and greedy reduction algorithm. We implemented the model and algorithm to determine the optimal temporary disposal places in Palembang City. The map of optimal temporary disposal places as the solution of the model was served in this paper.