Location optimization algorithm for emergency signs in public facilities and its application to a single-floor supermarket

doi:10.1016/j.firesaf.2008.05.006

Fire Safety Journal

Volume 44, Issue 1, January 2009, Pages 113-120

https://doi.org/10.1016/j.firesaf.2008.05.006 Get rights and content

Abstract

Although emergency signs are believed to play an important role in ensuring public safety in facilities during emergencies, in practice, specific and clear standards for placing emergency signs have not yet been established. This paper developed a heuristic algorithm based on the Lagrangian relaxation algorithm for optimizing emergency sign locations with consideration of light-occlusion effects. A cellular automaton (CA) evacuation model was then introduced, and based on this model, the evacuation efficiency of the optimized locations of emergency signs derived from the algorithm was verified, and was compared with the evacuation efficiencies of the same supermarket without and with existing emergency signs. The results showed that the proposed algorithm greatly enlarged the coverage of emergency signs and improved the evacuation efficiency. It was concluded that the proposed algorithm with consideration of light-occlusion effects is valid for application to the problem of location optimization of emergency signs in single-floor facilities.

Introduction

As a precaution against the possibility of mass accidents occurring in public facilities and to reduce any resultant losses, emergency management is becoming increasingly important. It not only attracts growing attention from governments, but is also of great concern to the public. Emergency signs are an essential component of public safety utilities and should not only provide guidance to evacuees to minimize loss of life, but should also support emergency personnel in rescuing evacuees [1], [2], [3], [4]. However, few codes can provide detailed guidelines for emergency sign locations in China, and the situation is similar in most developing countries. Only in national design codes, such as the Chinese design code for fire protection of high-rise civil architecture or that for emergency signs, are some general guidelines given; e.g., “Exit signs are needed at the exits of a large public building”, “The distance between the emergency signs on the walkway should be no more than 20 m”, etc. [5], [6].

Even following these general guidelines, it is still hard to obtain a solution for locating emergency signs in such a way as to respond exactly to the actual layout of a public facility. Besides, although some studies have pointed out the important role of emergency signs in the evacuation process and way finding [7], [8], [9], [10], [11], [12], few studies have attempted to explore the theory and methods for determining the best locations of emergency signs. As a result, the locations of emergency signs in public facilities are still limited to experts’ experience, which sometimes may not effectively help people to evacuate when an accident happens. It is highly desirable to solve the location optimization problem for emergency signs in public facilities, especially for developing countries, where budgets for emergency management are limited.

The location optimization for emergency signs can be considered as being of the maximal covering location problem (MCLP) type, which was originally proposed by Church and ReVelle [13] and is a well-studied problem in the field of location–allocation modeling [14], [15]. In MCLP, some discrete demand points in general are assumed covered by a facility if these points are within a predefined distance from at least one of the existing facilities. The objective of MCLP is to locate p facilities in the best places so that the maximal possible demand points can be covered. Similarly, the objective of location optimization for emergency signs is to maximize the light coverage of signs by locating emergency signs in the best places, where more coverage is assumed to allow more possibility for evacuees to be guided, to lead to more efficient evacuation. Therefore, it is reasonable to regard the location problem of emergency signs as a MCLP. However, it should be noted that emergency sign location optimization is more complicated than conventional MCLP because of the existence of obstacles, such as high shelves and hanging posters, which may influence the light coverage of emergency signs.

Based on what is mentioned above, this paper presents a Lagrangian relaxation algorithm to find the best locations for emergency signs in public facilities with consideration of the light-occlusion effect. Further, to assess the validity of the locations of emergency signs calculated by the new algorithm, a computer-based evacuation simulation with a cellular automaton (CA) model was employed and applied to compare the evacuation efficiencies in the case of a supermarket under three scenarios of emergency sign locations: (1) no emergency signs, (2) the existing locations, and (3) optimized locations.

Section snippets

Maximal covering location problem for emergency signs

The location optimization problem of emergency signs can be described as follows: in a given network G(V, A), V is the index set of all vertices, |V|=m the number of vertices in the network, and A the index set of all edges. Any vertex k (k∈V) is defined both as a potential location of an emergency sign, as well as a demand point that must be covered by an emergency sign. I is the index set of all demand points and J the index set of all potential locations of emergency sign. I∈V, J∈V, and I∪J=V

Introduction to the evacuation model

A simulation model to analyze evacuees’ behaviors in a public facility was developed based on the CA model [21]. CA is a discrete, decentralized, and spatially extended system consisting of large numbers of simple identical components with local connectivity. One of the advantages of CA-based simulation is that it is carried out according to several specified regulations instead of complex differential equations [22], [23], [24], [25]. In addition, the CA-based evacuation model is grid based

Simulation result of location optimization for emergency signs

Taking the supermarket shown in Fig. 7 as a case, the location optimization for emergency signs was analyzed, and its effect on guiding evacuation was evaluated using the CA-based evacuation model described in Section 3. The evacuation was simulated and the results were compared under three guidance scenarios: without emergency signs; with real existing emergency signs; and with optimized emergency signs.

Fig. 7 presents the layout of a supermarket case with length 73 m and width 49 m. There are

Conclusion and discussion

Although emergency signs play an important role in ensuring safety in public facilities, there are no specific and clear standards for emergency sign location, which may inhibit the expected function of emergency signs to some extent. Because the problem of locating emergency signs is quite similar to the MCLP, this paper proposed a heuristic algorithm based on the Lagrangian relaxation algorithm allowing for light-occlusion effects, which can be applied to emergency signage location in public

Acknowledgment

This study was supported by National Science and Technique Supporting Program (2006BAJ10B03), Ministry of Science and Technique, China.

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Location optimization algorithm for emergency signs in public facilities and its application to a single-floor supermarket

Abstract

Introduction

Section snippets

Maximal covering location problem for emergency signs

Introduction to the evacuation model

Simulation result of location optimization for emergency signs

Conclusion and discussion

Acknowledgment

Improving environmental information: effects of signs on perceived crowding and behavior

Environ. Behav.

The impact of exit instructions and number of exits in fire emergencies: a computer simulation investigation

J. Environ. Psychol.

Occupant evacuation and orientation problems in large halls—an exhibition building case study

Fire Mater.

A game theory based exit selection model for evacuation

Fire Saf. J.

Toward the characterization of building occupancies for fire safety engineering: capability of people with disabilities to read and locate exit signs

Fire Technol.

A study of evacuation from large retail stores

Fire Saf. J.

The impact of exit instructions and number of exits in fire emergencies: a computer simulation investigation

J. Environ. Psychol.

Visibility of exit sighs in clear and smoky conditions

J. Illum. Eng. Soc.

Effects of signage and floor-plan configuration on wayfinding accuracy

Environ. Behav.

The maximal covering location problem

Pap. Reg. Sci. Assoc.

Strategic facility location: a review

Eur. J. Oper.

Network and Discrete Location: Models Algorithms and Applications