The location set covering problem continues to be an important and challenging spatial optimization problem. The range of practical planning applications underscores its importance, spanning fire station siting, warning siren positioning, security monitoring and nature reserve design, to name but a few. It is challenging on a number of fronts. First, it can be difficult to solve for medium to l...

To improve the application of the maximal covering location problem (MCLP), several capacitated MCLP models were proposed to consider the capacity limits of facilities. However, most of these models assume only one fixed capacity level for the facility at each potential site. This assumption may limit the application of the capacitated MCLP. In this article, a modular capacitated maximal coveri...

This paper presents a hybrid algorithm that combines a metaheuristic and an exact method to solve the Probabilistic Maximal Covering Location-Allocation Problem. A linear programming formulation for the problem presents variables that can be partitioned into location and allocation decisions. This model is solved to optimality for small and medium-size instances. To tackle larger instances, a f...

Previous covering models for emergency service consider all the calls to be of the same importance and impose the same waiting time constraints independently of the service's priority. This type of constraint is clearly inappropriate in many contexts. For example, in urban medical emergency services, calls that involve danger to human life deserve higher priority over calls for more routine inc...

We compare heuristics based on Lagrangean and surrogate relaxations of the Maximal Covering Location Problem (MCLP). The Lagrangean relaxation of MCLP used in this paper has the integrality property and the surrogate relaxed problem we solve is the LP relaxation of the original 0ÿ1 knapsack problem. The heuristics were compared using 331 test problems available in the literature, corresponding ...

Capacitated covering models aim at covering the maximum amount of customers’ demand using a set of capacitated facilities. Based on the assumptions made in such models, there is a unique scenario to open a facility in which each facility has a pre-specified capacity and an operating budget. In this paper, we propose a generalization of the maximal covering location problem, in which facilities ...

The Maximal Covering Location Problem (MCLP) has the objective of maximizing the total demand volume covered by a facility within a maximum allowable travel distance, S. In this paper, three sets of data 30-node, 324-node and 818-node networks with no existing facilities are analyzed as the capacitated model of MCLP (CMCLP) and first solved by the commercial optimization software, CPLEX. As the...

Abstract: Hub location problem is one of the most important problems in the areas of logistics and telecommunication network design. In this paper, we address the single allocation maximal covering hub location problem in which the objective is to maximise the amount of covered flows associated with origin-destination pairs in a hub-and-spoke network using a fixed number of hub facilities. Two ...