Modeling the Emergency Service Network of Police Special Forces Units for High-Risk Law Enforcement Operations

Stanimirović, Zorica; Grujičić, Igor; Trifunović, Darko

doi:10.3138/infor.52.4.206

Cited by 6 publications

(35 citation statements)

References 34 publications

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“…In this paper, we consider a generalization of the problem of establishing the network of emergency service units that was introduced by Stanimirović et al [33]. The authors of [33] deal with the problem of designing the network of the Police Special Forces Units (PSFUs) in the Republic of Serbia. A set of potential locations for establishing PSFU units is given, and a set of cities to be allocated to established units.…”

Section: Introductionmentioning

confidence: 99%

“…The number of the PSFUs to be located is limited by a given constant, and according to the most common situation in practice, it is assumed that each city will be assigned to its closest established PSFU unit. The model proposed in [33] also involves penalties in the case that a city is assigned to a PSFU unit that lies outside given range that ensures an efficient PSFU reaction. Differently from studies that optimize emergency service systems from customers' point of view, i.e., minimize the maximum distance between customer and service provider [8,9,11,19], Stanimirović et al [33] deal with designing the network of emergency units from providers' point of view [5,13,26].…”

Section: Introductionmentioning

confidence: 99%

“…The model proposed in [33] also involves penalties in the case that a city is assigned to a PSFU unit that lies outside given range that ensures an efficient PSFU reaction. Differently from studies that optimize emergency service systems from customers' point of view, i.e., minimize the maximum distance between customer and service provider [8,9,11,19], Stanimirović et al [33] deal with designing the network of emergency units from providers' point of view [5,13,26]. In practice, emergency units are required to travel longer distances than others to reach an assigned city, or to react in cities with higher number of incidents, and therefore, the workload of emergency units will be most likely unequal.…”

Section: Introductionmentioning

confidence: 99%

“…On the other side, all units are generally equally paid, regardless of amount of their workload during a shift. Therefore, the objective of the model proposed in [33] is to minimize the maximal load of a PSFU unit, while preserving the efficiency of the emergency system. In the literature, there are examples of location models that involve workload balance of facilities in the objective [1,16,20,21].…”

Section: Introductionmentioning

confidence: 99%

“…Capturing data uncertainty in deterministic models may be achieved in different approaches that were proposed in the literature in past years [7,19,27,31,36]. Starting from deterministic PSFU location model, Stanimirović et al [33] also proposed a robust optimization model that captures the uncertainty of the number of incidents in each city. More precisely, in [33] it is assumed that the coefficients representing the number of criminal incidents in are subject to uncertainty, and they are modeled as independent, symmetric and bounded random variables with unknown distribution.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid metaheuristic method for solving a multi-period emergency service location problem

Mišković

Stanimirović

2016

ITC

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This study deals with the problem of establishing the network of emergency service units. The goal of the basic problem proposed in the literature is to locate certain number of units at given discrete points of the region and to allocate cities to established units, in order to balance the load of established emergency units. Having in mind that emergency units work in shifts, we extend the basic model to a multi-period model and involve additional constraints on the number of units to be located. Since, in practice, the number of emergency incidents varies on daily or monthly basis, we consider the uncertainty of the number of incidents and propose a robust integer programming formulation of the multi-period model, which controls the deviation of objective value under uncertainty of input data. In order to solve both deterministic and robust variant of the problem, we design an efficient hybrid metaheuristic method based on combination of Particle Swarm Optimization method (PSO) and Reduced Variable Neighborhood Search (RVNS). Computational results show that the proposed hybrid PSO-RVNS method quickly reaches all known optimal solutions obtained by CPLEX solver, and provides solutions for instances that remained out of reach of CPLEX. In the single-period case, PSO-RVNS outperforms existing metaheuristic method from the literature in the sense of CPU time. Short running times of PSO-RVNS and high-quality solutions indicate the efficiency of the proposed hybrid metaheuristic approach when solving the considered problem. Results presented in this study may help security experts and emergency managers to design an efficient and sustainable emergency system.

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Section: Introductionmentioning

confidence: 99%