Optimized Design of Large-Scale Social Welfare Supporting Systems on Complex Networks

Janáček, Jaroslav; Jánošíková, Ľudmila; Buzna, Ľuboš

doi:10.1007/978-1-4614-0754-6_12

Cited by 8 publications

(6 citation statements)

References 31 publications

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“…The likelihood of the occurrence of emergency cases within a certain geographic area is frequently assumed to be proportional to the population [18,48]. This is a practical modelling assumption due to the high availability of population data.…”

Section: Locations Of Emergency Casesmentioning

confidence: 99%

On the Modelling of Emergency Ambulance Trips: The Case of the Žilina Region in Slovakia

Buzna

Czimmermann

2021

Mathematics

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The efficient operation of emergency medical services is critical for any society. Typically, optimisation and simulation models support decisions on emergency ambulance stations’ locations and ambulance management strategies. Essential inputs for such models are the spatiotemporal characteristics of ambulance trips. Access to data on the movements of ambulances is limited, and therefore modelling efforts often rely on assumptions (e.g., the Euclidean distance is used as a surrogate of the ambulance travel time; the closest available ambulance is dispatched to a call; or the travel time estimates, offered by application programming interfaces for ordinary vehicles, are applied to ambulances). These simplifying assumptions are often based on incomplete data or common sense without being fully supported by the evidence. Thus, data-driven research to model ambulance trips is required. We investigated a unique dataset of global positioning system-based measurements collected from seventeen emergency ambulances over three years. We enriched the data by exploring external sources and designed a rule-based procedure to extract ambulance trips for emergency cases. Trips were split into training and test sets. The training set was used to develop a series of statistical models that capture the spatiotemporal characteristics of emergency ambulance trips. The models were used to generate synthetic ambulance trips, and those were compared with the test set to decide which models are the most suitable and to evaluate degrees to which they fit the statistical properties of real-world trips. As confirmed by the low values of the Kullback–Leibler divergence (0.004–0.229) and by the Kolmogorov–Smirnov test at the significance level of 0.05, we found a very good fit between the probability distributions of spatiotemporal properties of synthetic and real trips. A reasonable modelling choice is a model where the exponential dependency on the population density is used to locate emergency cases, emergency cases are allocated to hospitals following empirical probabilities, and ambulances are routed using the fastest paths. The models we developed can be used in optimisations and simulations to improve their validity.

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Section: Locations Of Emergency Casesmentioning

confidence: 99%

On the Modelling of Emergency Ambulance Trips: The Case of the Žilina Region in Slovakia

Buzna

Czimmermann

2021

Mathematics

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“…M., 1995;Drezner, 1995). To evaluate the optimality error and the time efficiency of the proposed reaggregation algorithm, we use the p-median problem, which is one of the most frequently studied and used location problems (Hakimi, 1965;Calvo and Marks, 1973;Berlin G N et al, 1976;Janáček et al, 2012). This problem includes all basic decisions involved in the service system design.…”

Section: The P-median Location Problemmentioning

confidence: 99%

“…subversion S1 (Janáček et al, 2012). For the region ofŽilina we add to our benchmarks also the case, when the aggregation is done at the level of individual municipalities (i.e.…”

Section: Large Location Problemsmentioning

confidence: 99%

Re-aggregation Approach to Large Location Problems

Cebecauer

Buzna

2015

Proceedings of the International Conference on Operations Research and Enterprise Systems

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The majority of location problems are known to be NP-hard. An aggregation is a valuable tool that allows to adjust the size of the problem and thus to transform it to the problem that is computable in a reasonable time. An inevitible consequence is the loss of the optimality due to aggregation error. The size of the aggregation error might be significant, when solving spatially large problems with huge number of customers. Typically, an aggregation method is used only once, in the initial phase of the solving process. Here, we propose new re-aggregation approach. First, our method aggregates the original problem to the size that can be solved by the used optimization algorithm, and in an each iteration the aggregated problem is adapted to achieve more precise location of facilities for the original problem. We use simple heuristics to minimize the sources of aggregation errors, know in the literature as, sources A, B, C and D. To investigate the optimality error, we use the problems that can be computed exactly. To test the efficiency of the proposed method, we compute large location problems reaching 80000 customers.

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“…The weighted p-median problem [6] is one of the most basic and important models for solving the problems related to the public service design [1]. The locations of at maximum p max servers servicing the set of customers J are to be selected from the set of candidate locations I.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…Designing public service systems, as for example, distribution systems, emergency medical systems, or to decide on positions of marshalling yards throughout the railway network, various types of location and allocation models can be used [1]. In general, this problem can be seen as an example of resource allocation problem, with a central planner.…”

Section: Introductionmentioning

confidence: 99%

Proportionally Fairer Public Service Systems Design

Buzna¹,

Koháni²,

Janáček³

2013

Komunikácie

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This paper focuses on the utilitarian solution of public service system design problem, obtained when maximising the sum of all utilities and proportionally fair-like solution, taking into account proportional changes in individual utilities. As an archetypal example of the optimisation problem, we are examining the weighted p-median problem, which is solved by the primary-dual based procedure. We use realistic largescale data describing the road network and spatial distribution of population. By comparing the resulting solutions, for selected range of parameters, we evaluate how costly it is to consider fairness criteria in the service system design. As for integer problems the proportional fairness scheme does not guarantee the existence of dominant optimal solution, we evaluate the close neighbourhood of obtained solutions. Based on these analyses we draw conclusions on the price of (proportionally-like) fair solutions and their stability.

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Optimized Design of Large-Scale Social Welfare Supporting Systems on Complex Networks

Cited by 8 publications

References 31 publications

On the Modelling of Emergency Ambulance Trips: The Case of the Žilina Region in Slovakia

On the Modelling of Emergency Ambulance Trips: The Case of the Žilina Region in Slovakia

Re-aggregation Approach to Large Location Problems

Proportionally Fairer Public Service Systems Design

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