A multicriteria spatial decision support system for solving emergency service station location problems

Abstract

Earthquakes occurring in urban areas constitute an important concern for emergency management and rescue services. Emergency service location problems may be formulated in discrete space or by restricting the potential location(s) to a specified finite set of points in continuous space. We propose a Multicriteria Spatial Decision Support System to identify shelters and emergency service locations in urban evacuation planning. The proposed system has emerged as an integration of the geographical information systems (GIS) and the multicriteria Decision-Making method of Preference Ranking Organization Method for Enrichment Evaluation IV (PROMETHEE IV). This system incorporates multiple and often conflicting criteria and decision-makers' preferences into a spatial decision model. We consider three standard structural attributes (i.e., durability density, population density, and oldness density) in the form of spatial maps to determine the zones most vulnerable to an earthquake. The information on these spatial maps is then entered into the ArcGIS software to define the relevant scores for each point with regards to the aforementioned attributes. These scores will be used to compute the preference functions in PROMETHEE IV, whose net flow outranking for each alternative will be inputted in ArcGIS to determine the zones that are most vulnerable to an earthquake. The final scores obtained are integrated into a mathematical programming model designed to find the most suitable locations for the construction of emergency service stations. We demonstrate the applicability of the proposed method and the efficacy of the procedures and algorithms in an earthquake emergency service station planning case study in the city of Tehran.

Multicriteria optimization approach to deploy humanitarian logistic operations integrally during floods

“…To develop this methodology, the following assumptions were made with the stakeholders: Affected areas are classified as in isolated (unreachable by ground transport) and nonisolated areas to let the stakeholders decide the type of vehicles to be used in the operations. The GIS procedure is able to determine locations of meeting points (i.e., transfer points) for different flood levels to link isolated areas with the connected network to facilitate evacuation under dynamic conditions (see Esmaelian et al., ). Available resources (i.e., emergency facilities and vehicles) and their capacities, locations, and costs are known in advance at every node of the proposed graph. Vehicles belong to different types (i.e., helicopters, buses, trucks, cars, and boats), are sufficient for the operations, or can be quickly allocated by the unique interagency decision maker, regardless if they belong to humanitarian organizations. They can work on specific humanitarian operations and within the chosen operation, these vehicles compete for the same space (i.e., ground vehicles compete for the same road infrastructure). Two types of available budget are considered and allocated in advance as part of an annual financial plan by authorities: Preparation budget is used for conditioning and preparation costs of facilities, while response budget is used for evacuation and distribution operations. Authorities recognize mainly the use of five types of relief kits: (a) food/water; (b) drugs; (c) personal hygiene items, such as toilet paper; (d) cleaning items; and (e) miscellaneous items, such as linens, fuel, and equipment (for further details, see Garrido et al., ). Facilities’ construction costs are mainly considered as structural disaster risk reduction strategies in the mitigation phase of disasters.…”

“…The GIS procedure is able to determine locations of meeting points (i.e., transfer points) for different flood levels to link isolated areas with the connected network to facilitate evacuation under dynamic conditions (see Esmaelian et al., ).…”

“…Furthermore, important efforts have been made to create risk maps through GIS to feed mathematical models with updated information from natural disasters (Coutinho‐Rodrigues et al., ; Esmaelian et al., ; Rodríguez‐Espíndola and Gaytán, ), but there are still opportunities to be addressed in their combined use. On the other hand, research has focused on either addressing humanitarian operations such as evacuation and inventory management (see Beamon and Kotleba, ; Huang et al., ), distribution operations (see Barbarosoğlu and Arda, ; Özdamar et al., ; Chang et al., ; Tzeng et al., ; Vitoriano et al., ; Liberatore et al., ; Garrido et al., ), and location of emergency facilities separately or combining only a few of them: location of shelters and evacuation operations (see Barbarosoğlu et al., ; Sakakibara et al., ; Balcik et al., ; Coutinho‐Rodrigues et al., ; Esmaelian et al., ). location of distribution centers and distribution operations (see Mete and Zabinsky, ; Nolz et al., ; Yushimito et al., ; Rodríguez‐Espíndola and Gaytán, ). …”

The Combination of Expert Judgment and GIS-MAIRCA Analysis for the Selection of Sites for Ammunition Depots

“…First of all, the initial decision matrix is designed (Table 13), and, afterwards, the criteria normalization is completed using Equations (26) and (27). Data shown in Table 13 represent average values of the location suitability obtained using GIS Zonal statistical operation from the reclassified evaluation criteria maps.…”

“…Determination of real evaluation Equation (27). (27) where n is the total number of criteria, m is the total number of alternatives.…”