Handbook of Optimization in Complex Networks pp 337-361 | Cite as

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

## Abstract

Our contemporary societies are supported by several systems of high importance providing large-scale services substantial for citizens everyday life. Typically, these systems are built or rely on various types of complex networks such as road networks, railway networks, electricity networks, communication networks etc. Examples of such systems are a set of emergency medical stations, fire or police stations covering the area of a state, social or administration infrastructure. The problem of how to design these systems efficiently, fairly, and reliably is still timely and it brings along many new research challenges. This book chapter presents a brief survey of optimization models and approaches applicable to the problem. We pay special attention to the methods based on the branch and bound principle and show how their computational properties can be improved. Furthermore, we discuss how some of these models can be rearranged in order to allow using the existing solving techniques as approximative methods. The presented numerical experiments are conducted on realistic data describing the topology of the Slovak road network. On the one hand, we hope that this chapter can come handy to researchers working in the area of complex networks, as it presents efficient methods to design public service systems on the networks. On the other hand, we can picture the benefits potentially resulting from the knowledge of the network properties and possibly being utilized in the algorithms design.

## Keywords

Public service systems Large-scale emergency systems## Notes

### Acknowledgements

The authors are grateful for the financial support provided by the Ministry of Education of the Slovak Republic (project VEGA 1/0361/10) and thank J. Slavík, P. Tarábek, M. Koháni, and two anonymous reviewers for thorough reading of the manuscript and the valuable comments.

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