A sample application for scheduling search and rescue teams in an earthquake disaster

Abstract

Keywords: Disaster Management; Earthquake; Staff Scheduling; Search and Rescue Teams; Goal Programming

Introduction

Disasters that occur suddenly are a situation that requires the coordinated work of many institutions and organizations. Türkiye is located between the African and Arabian plates and the Eurasian plates. Türkiye is an earthquake country that frequently experiences tectonic earthquakes caused by plate movement. According to the Earthquake Zones Map,

92% of the country is in earthquake zones, and 95% of the population lives under earthquake risk [1]. An earthquake is an event that causes loss of life by shaking the surface that we know as immobile and damaging the structures on it [1]. The time of the earthquake’s occurrence is unknown, but all the work done to reduce the damage it may cause is the subject of disaster management [2]. Disaster management, which is a dynamic and

*Corresponding author. *E-mail address: tamereren@gmail.com, meakdas9@gmail.com This paper was recommended for publication in revised form by Regional Editor Omid Mahian Published by Yıldız Technical University Press, İstanbul, Turkey Copyright 2021, Yıldız Technical University. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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multifaceted process, includes organizing and managing the activities needed to reduce the adverse effects of disasters. Search and rescue, first aid, evacuation, prevention of secondary disasters, etc., work is carried out by teams. Disasters that cause significant damage make managing search and rescue efforts difficult. This reveals the difficulty of sending teams to disaster areas. Emergencies are sudden, uncertain, and devastating. Search and rescue teams often face challenging tasks in multiple and scattered disaster areas. Because disaster and relief situations are complex, emergency decision-makers must reasonably and quickly assign teams to disaster areas. Therefore, determining the optimum distribution of teams is a valuable research topic [3]. This situation requires an effective organization to send swiftly teams to areas requiring search and rescue [4]. Search and rescue efforts, which started immediately after the buildings collapsed and the people were trapped in the buildings, started and continued sequentially and continuously. As soon as the disaster occurs, search and rescue efforts begin with the people in the immediate vicinity rushing to help with their means. With effective communication and transportation means, these studies continue with regional or national support after local disaster and emergency services reach the region [5]. It has been seen that the 6 February 2023 Kahramanmaraş earthquakes that occurred recently on the Eastern Anatolian Fault (EAF) caused significant material and moral losses and it is essential to direct the teams quickly. According to scientific predictions, the stress emitted by fault lines broken in earthquakes in this region may have been transferred to other nearby fault lines. EAF has the potential to produce large earthquakes. The province of Elazığ, located on this fault, is in the first-degree earthquake zone and is within the impact area of many active faults. One of the earthquakes that will significantly affect Elazığ Province is the earthquakes that may occur in the Palu segment between Gökdere and Hazar Lake. EAF line is very close to the Palu and Kovancılar districts of Elazığ Province. The geological structure of the center of Palu increases the destructiveness in case of an earthquake. These reasons increase the effect of the earthquake. In addition, alluvial ground in the plains of the center of Elazığ will cause more building damage in possible earthquakes [6]. To reduce post-earthquake chaos and information pollution, earthquake scenarios are produced by the AFAD Earthquake Department. Scenarios are analyzed with the AFAD-RED analysis program. The outputs of the program produce estimation results for potential losses. With these results, it is aimed to send the teams to the right disaster areas as soon as possible. In this study, the province of Elazığ, a first-degree earthquake zone, is handled. In the scenario used, it is known that 8 districts will be destroyed in an earthquake with a magnitude of 7.3 in Elazığ. The problem of scheduling the AFAD search and rescue teams to be dispatched to the disaster areas where the destruction occurred is discussed to keep the losses to a minimum. The problem of dispatching teams

to districts with collapsed buildings is NP-hard; therefore, goal programming is used. A mathematical model is created with the goal programming method to send the teams to the districts where the collapsed buildings are located. This problem aims to dispatch the appropriate number of teams to the right disaster areas.

Literature Review

This study discusses the scheduling of search and rescue teams in disaster management, and the literature review on the subject is presented in this section. [7] aimed to address the assignment problem during the search and rescue period to reduce the earthquake’s death toll and allocate resources to earthquake zones. He created an optimized resource schedule using simulated annealing and tabu search heuristics. [8] aimed at the logistics system that assists disaster victims, which is formulated as a multi-objective optimization problem, and one of the objective functions is to minimize the total travel time. [9] aimed at a decision support system that aims to plan rescue units and assign units to incidents. They proposed a nonlinear optimization model and proposed a Monte Carlo-based heuristic solution. [10] aimed to allocate and schedule recovery units with a biased random key genetic algorithm to minimize the sum of the fuzzy processing times of the events and the weighted completion time according to the severity level. [11] aimed to allocate emergency units to the scene, and casualties at the scene to get the injured out of the red and yellow triage in the first hours of the disaster. [12] aimed to a model for the assignment of rescue units to multiple disaster areas, taking into account the compatibility between the skills and duties of the rescuers. [13] aimed to allocate and schedule to minimize completion time in response to rescue teams. They used the complex integer programming model and the GRASP metaheuristic method. [14] aimed at the problem of allocation and scheduling of rescue units with the learning effect. The problem is likened to the disconnected parallel machine scheduling and traveling salesman problem. They benefited from multi-objective goal programming and robust optimization methods. [15] aimed at the task assignments of rescue teams in local search and rescue operations. They created three scenarios with different earthquake magnitudes and uncertainty. [16] aimed at the problem of scheduling the teams conducting urban search and rescue operations in an earthquake disaster. They used mathematical programming to decide which team would be dispatched to which scene. [17] aimed to determine the search and rescue teams coming to Türkiye for international assistance in disaster management planning. Multicriteria decision-making techniques AHP and TOPSIS methods were used to determine the teams. [4] aimed at dispatching rescuers to multiple disaster areas and different rescue points. They used the evidence-based best-worst method and Dempster-Shafer theory-based modeling to

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maximize rescue time satisfaction and rescuer competence for dispatching rescuers to multiple disaster sites. [18] with queuing theory, aimed to determine the number of rescuers in search and rescue operations. The damages to the buildings, the number of injured, the determination of the service period, the simulation model design, and the victims’ survival rates were calculated and compared with the duration of the rescue operations. [19] aimed at the problem of assigning rescue units with the data from the flood disaster in Iran. Fuzzy robust optimization and hybrid metaheuristic algorithms minimize the sum of weighted completion times of recovery operations. [20] aimed at the assignment problem of rescuers, taking into account the skill levels, preferences, joint knowledge, and rescue operation time of the rescuers. [21] aim at the scheduling problem of search and rescue and psychosocial support teams in areas with collapsed buildings in the Erzincan earthquake. They used goal programming method as solution method. [22] aim at the scheduling problem of search and rescue teams in the disaster districts where the destruction occurred in the Aydın earthquake, the epicenter of which was the town of Efeler, using the target programming method. In addition, applications were made in different fields by using various methods of personnel scheduling, which is the subject of this study. It is desired to give brief information about the application areas of these studies. In the energy sector [23], in the retail sector [24], in the manufacturing sector [25, 26], in the shift scheduling [27, 28], in the nurse scheduling [29, 30], in the service sector [31, 32], in the security staff scheduling [33] applications were made in the textile sector [34]. In addition, [35] conducted a literature review study with the goal of programming methods in service systems and [36] with personnel scheduling problems. The goal programming method used in this study has also been used to solve many other problems. If we talk about some studies to give information, an integrated approach to supplier selection with goal programming and [37, 38], for project selection [39, 40], surgical operation scheduling with goal programming and constraint programming [41], in sustainable personnel scheduling [42], in the operating room scheduling with surgical team problem [43] handled their studies with the goal programming method. The summary of the research articles cited in the literature review section is given in Table 1.

to zero, and they cannot take a negative value. In the objective function, these deviation values are tried to be minimized. The formulation of the goal programming method is shown in Equations 1-3 [44]. xj: j.decision variable wij: i.target j.decision variable coefficient ki: the desired value for the target i. di+: positive deviation value of i.target di-: negative deviation value of i.target (1)

(3) Equation 1 expresses the objective function of the model. Equation 2 is the target constraint ki is the righthand side value that is trying to be reached. If Equation 3 is the hard constraint in the model, the model is unsolvable.

Application

In the application, the province of Elazığ, located in the 1st-degree earthquake zone and frequently exposed to earthquakes, is handled. It is desired to keep the losses to a minimum due to a possible Elazığ earthquake. Therefore, the study used the outputs of an earthquake scenario created by AFAD. The flowchart of the problem is given in Figure 1.

GOAL Programming

Problem Identification The problem of scheduling the search and rescue teams that will be dispatched to the districts where the destruction occurred when an earthquake with a magnitude of

Evaluation Of Solution Results

According to the solution results obtained, are dispatched 4 teams to Elazığ Alacakaya district, 1 team to Elazığ Arıcak district, 17 teams to Elazığ Karakoçan district, 150 teams to the Elazığ Kovancılar district, 28 teams to Elazığ Maden district, 30 teams to Elazığ Elazığ Merkez district, 148 teams to Elazığ Palu district and 1 team to Elazığ Palu district. The target constraints between constraints (3) and (13) are provided. 40 of the 150 teams sent to Kovancılar district are sent from the Union Directorate. 16 of the 28 teams sent to Maden district are sent from the Union Directorate. 16 of the 30 teams sent to Merkez district are sent from the Union Directorate. 40 of the 148 teams sent to Maden district are sent from the Union Directorate. The solution results are shown in Figure 2.

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Conclusion

An effective management system is needed to reduce the negative effects of the disaster. Disaster management, a versatile and dynamic system, consists of four stages: damage and risk reduction, preparedness, response, and recovery. Different studies are carried out in each of these stages. In this study, search and rescue teams, which are actively involved in the intervention phase, are discussed. When the studies in the literature are examined, this study will likely guide the search and rescue teams in disaster management in personnel scheduling. In this study, a 7.3 magnitude earthquake scenario that will occur in the Palu segment of Elazığ Province is handled. 8 disaster areas are estimated to be affected by the earthquake. The problem of scheduling AFAD search and rescue teams to these regions has been addressed. The problem is NP-hard; therefore, the goal programming method is used. The application is continued by using the statistical outputs of this scenario, which is created with an analysis program by the AFAD Earthquake Department. According to the solution results obtained, are dispatched 4 teams to Elazığ Alacakaya district, 1 team to Elazığ Arıcak district, 17 teams to Elazığ Karakoçan district, 150 teams to the Elazığ Kovancılar district, 28 teams to Elazığ Maden district, 30 teams to Elazığ Elazığ Merkez district, 148 teams to Elazığ Palu district and 1 team to Elazığ Palu district. This study assumes that search and rescue operations are carried out in the ruined buildings. However, suppose there is a disaster victim (disabled, elderly, paralyzed, etc.) who cannot go out by his means in heavily damaged buildings. In that case, rescue works can be carried out. 2 out of 16 provinces with a union directorate are excluded because search and rescue teams in the disaster-affected region cannot be included because they are responsible for their regions. While planning, the maximum number is calculated while determining the number of teams to be dispatched to the areas due to the uncertain and destructive nature of the disaster.

The occurrence of earthquakes that caused significant losses in the past is a herald of earthquakes of similar magnitudes in the future. To be a disaster-resilient society, it is necessary to prepare for disasters by making essential pre-disaster planning. In future studies; • Unlike this study, which is carried out considering the ruined buildings, older people, paralyzed, disabled, etc., In the case of disaster victims, the study can be expanded by adding new constraint(s) to the model. • If the number of teams is insufficient, more teams can be assigned to disaster areas where destruction is high using the weighted and priority goal programming method. • Since the mathematical models created can be used for various scenarios in different earthquake regions, similar studies can be conducted, especially considering the regions where scientists expect earthquakes shortly. • Appointments and schedules can be created for other teams involved in disaster management, such as firefighters and health teams, who undertake different tasks. While creating these charts, they can be combined with the shortest path problems by considering the positions of the teams to be assigned according to the disaster areas and the team assignment.

Nomenclature

AFAD Disaster and Emergency Management Presidency EAF Eastern Anatolian Fault

Acknowledgement

I want to thank Adana AFAD search and rescue technician Hikmet Eroğlu, who shared the necessary information during the implementation phase of the Research. Kırıkkale University’s BAP Coordination Unit supports this study.

Data Availability Statement

The authors confirm that the data that supports the findings of this study are available within the article. Raw data that support the finding of this study are available from the corresponding author, upon reasonable request.

Conflict Of Interest

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethics

There are no ethical issues with the publication of this manuscript.

Sigma J Eng Nat Sci, Vol. 42, No. 5, pp. 1555−1562, October, 2024

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