A Two-Phase Optimization Method for Solving the Multi-Type Maximal Covering Location Problem in Emergency Service Networks

Stanimirović, Zorica; Mišković, Stefan; Trifunović, Darko; Veljović, Veselin

doi:10.5755/j01.itc.46.1.13853

Cited by 4 publications

(1 citation statement)

References 24 publications

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“…Nogueira, Pinto, and Silva (2018) deal with this problem on a case of ambulance base locations in Brazil. Similarly, Stanimirovic et al (2017) studied the problem to choose locations for establishing emergency units on real-life instances obtained from two networks of police units in Montenegro and Serbia. A two-stage stochastic programming location-allocation model is proposed by Boujemaa et al (2018) to simultaneously determine the location of ambulance stations, the number and the type of ambulances to be deployed, and the demand areas served by each station.…”

Section: Literature Reviewmentioning

confidence: 99%

Fair Facility Allocation in Emergency Service System

Janáček

Gábrišová

Plevný

2020

Journal of Business Economics and Management

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The request of equal accessibility must be respected to some extent when dealing with problems of designing or rebuilding of emergency service systems. Not only the disutility of the average user but also the disutility of the worst situated user must be taken into consideration. Respecting this principle is called fairness of system design. Unfairness can be mitigated to a certain extent by an appropriate fair allocation of additional facilities among the centres. In this article, two criteria of collective fairness are defined in the connection with the facility allocation problem. To solve the problems, we suggest a series of fast algorithms for solving of the allocation problem. This article extends the family of the original solving techniques based on branch-and-bound principle by newly suggested techniques, which exploit either dynamic programming principle or convexity and monotony of decreasing nonlinearities in objective functions. The resulting algorithms were tested and compared performing numerical experiments with real-sized problem instances. The new proposed algorithms outperform the original approach. The suggested methods are able to solve general min-sum and min-max problems, in which a limited number of facilities should be assigned to individual members from a finite set of providers.

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Section: Literature Reviewmentioning

confidence: 99%