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Means Clustering Algorithm to Establish Humanitarian Support Centers in Large Regions at Risk in Mexico

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Means Clustering Algorithm to Establish Humanitarian Support Centers in Large Regions at Risk in Mexico Hindawi Journal of Optimization Volume 2018, Article ID 3605298, 14 pages https://doi.org/10.1155/2018/3605298 Research Article Extended GRASP-Capacitated �-Means Clustering Algorithm to Establish Humanitarian Support Centers in Large Regions at Risk in Mexico Santiago-Omar Caballero-Morales , Erika Barojas-Payan, Diana Sanchez-Partida , and Jose-Luis Martinez-Flores Universidad Popular Autonoma del Estado de Puebla, A.C., Postgraduate Department of Logistics and Supply Chain Management, Puebla, Mexico Correspondence should be addressed to Santiago-Omar Caballero-Morales; [email protected] Received 9 July 2018; Revised 25 November 2018; Accepted 4 December 2018; Published 20 December 2018 Guest Editor: Morteza Ghobakhloo Copyright © 2018 Santiago-Omar Caballero-Morales et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Mexico is located within the so-called Fire Belt which makes it susceptible to earthquakes. In fact, two-thirds of the Mexican territory have a signifcant seismic risk. On the other hand, the country’s location in the tropical zone makes it susceptible to hurricanes which are generated in both the Pacifc and Atlantic Oceans. Due to these situations, each year many communities are afected by diverse natural disasters in Mexico and efcient logistic systems are required to provide prompt support. Tis work is aimed at providing an efcient metaheuristic to determine the most appropriate location for support centers in the State of Veracruz, which is one of the most afected regions in Mexico. Te metaheuristic is based on the �-Means Clustering (KMC) algorithm which is extended to integrate (a) the associated capacity restrictions of the support centers, (b) a micro Genetic Algorithm �GA to estimate a search interval for the most suitable number of support centers, (c) variable number of assigned elements to centers in order to add fexibility to the assignation task, and (d) random-based decision model to further improve the fnal assignments. Tese extensions on the KMC algorithm led to the GRASP-Capacitated �-Means Clustering (GRASP-CKMC) algorithm which was able to provide very suitable solutions for the establishment of 260 support centers for 3837 communities at risk in Veracruz, Mexico. Validation of the GRASP-CKMC algorithm was performed with well-known test instances and metaheuristics. Te validation supported its suitability as alternative to standard metaheuristics such as Capacitated �-Means (CKM), Genetic Algorithms (GA), and Variable Neighborhood Search (VNS). 1. Introduction Mexico is located within the so-called Fire Belt of the Pacifc and within the tropical zone. Tis makes the country A phenomenon or disturbing agent is defned as an aggressive susceptible to a great variety of disturbing agents of natural andpotentiallyharmfulphysicalevent,naturalorderived origin [3]: from human activity, which can cause loss of life or injury, material damage, serious disruption of social and economic (a) Two-thirds of the country have signifcant seismic life, or environmental degradation. Tus, these agents can risks. have the following origins [1, 2]: (b) Coastal regions are frequently afected by hurricanes (a) Natural: geological, hydrometeorological, and astro- which are generated in the Pacifc and Atlantic nomical. Oceans. (b) Anthropogenic: chemical-technological, health-eco- Due to its geographical location, geological characteris- logical, and social-organizational. tics, and the complex morphology of its territory, the State of 2 Journal of Optimization Table 1: Declarations of natural disasters: 2014-2017 [5]. Year Description FONDEN (Mexican Pesos) 2014 01. Severe rain and fuvial food in October 13-16 193,636,015.00 2015 01. Severe rain in March 11-12 1,610,707,729.00 02. Severe rain in March 21-23 and severe rain and fuvial food in March 25-27 03. Severe rain and fuvial food in June 11-14 04. Hillside movement in July 9-13 05. Hillside movement in September 16-18 06. Severe rain and fuvial and rain food in October 16-21 07. Severe rain and fuvial and rain food in October 18-24 2016 01. Hillside movement in August 5-7 860,195,408.00 02. Severe rain and fuvial food in August 5-7 03. Severe rain in September 27-28 2017 01. An earthquake with magnitude 8.2 on September 7 496,947,819.20 02. Hurricane “Katia” - severe rain and fuvial food in September 8-12 03. Hillside movement from September 27 to October 9 04. Severe rain and fuvial food from September 27 to October 9 05. Fluvial food in October 11-15 06. Severe rain in October 11 Total 3,161,486,971.20 Veracruz in Mexico is exposed to natural phenomena such which consist of inventory and location planning of as earthquakes, volcanic eruptions, foods, and landslides. resources, are performed. Te presence of hydrometeorological phenomena is very (2) Pre-impact phase: warning to the population based common in Veracruz, which leads to frequent afectations. In on prediction mechanisms and implementation of response to the presence of disturbing natural phenomena, in mitigating measures are performed. Mexico the Natural Disasters Fund (FONDEN) was created. Tisisafnancialinstrumentwhosepurposeistoprovide (3) Disaster impacts the community. relief supplies and assistance in emergency and disaster sit- (4) Emergency phase: isolation, rescue, and external uations. In Veracruz, the rules of the Fund for the Prevention assistance are performed. It is ofen the phase in which of Natural Disasters (FOPREDEN) are an instrument that local resources are overwhelmed and external aid is aims to revitalize initiatives aimed at preventing disasters and required to reduce the number of fatalities. seeks to optimize the use of available fnancial resources and (5) Reconstruction phase: activities focused on recov- magnify the results linked mainly to the preservation of the ering the normal duties of the community are per- life and physical integrity of people, as well as that of public formed. services and infrastructure and the environment [4]. As of 2017 FONDEN has authorized resources for more Before the disaster occurs, it is important to have facilities than three billion of Mexican pesos to support the road, with an optimal inventory of products of frst necessity to educational sectors, forestry, hydraulic, naval, housing, and support the survival of the people who will be afected. urban infrastructure in Veracruz due to the signifcant occur- Also, afer the disaster occurs, it is important to have the rence of natural disasters within the period 2014-2017.Table 1 infrastructure to resupply the facilities and transport afected presents an overview of the historical phenomena within this people to other facilities as needed. period and the resources provided. Hence, among the most critical decisions and resources Standard protocols to be performed before, during, and to provide relief to the afected communities in Veracruz, afer a disaster involve diferent logistic processes. Tese are prepositioning of warehouses must be performed. Tis allows performed in the diferent phases of a disaster [6, 7]: the protection of supplies and the efcient and timely supply of products to cover the basic needs of the people afected (1) Interdisaster phase: processes are performed in which by the disturbing phenomenon. Within the activities to the elaboration of the map of risks for the com- be performed in these warehouses or support centers, the munity is highlighted. Also the Plans of Emergency, following can be mentioned: Journal of Optimization 3 (1) Identifcation, labeling, and location of the necessary (ii) Te facility location problem was also addressed supplies to attend the emergency. by [17] that presented a multiobjective optimization model to solve a multidepot emergency facilities (2) Consolidation of load and change of means of trans- location-routing problem. Due to the inherent com- port. putational complexity of this model an approximate (3) Delivery scheduling for the supplies. method based on the metaheuristic of Genetic Algo- rithms (GAs) was developed. Likewise, the warehouse must have an information and (iii) Prepositioning or relief assets was studied in [11] to inventory control system which must be updated, through optimize the transportation of afected people to relief the control of inventories. Te activation of a prepositioned centers. Te proposed stochastic model considered warehouse is the responsibility of State Civil Protection optimization of resources such as personnel and with selection criteria for its allocation such as (a) being vehicles to minimize casualties. located outside the risk area, (b) having a solid and roofed construction in compliance with safety parameters, (c) being (iv) In [18] the aspect of considering containers as storage accessible through favorable conditions for transport loading facilities was studied, and a mathematical model was and unloading, (d) being ventilated, illuminated, and without proposed to determine the locations of supply points water seepage risk, (e) being located far away from food- and the quantity of containers and relief supplies prone areas, (f) being free of pollution or plague, and (g) assigned to each supply point under the minimum having space to facilitate the mobility, cleaning, and classi- distance criteria. fcation of products [8, 9]. Minimization of distance between (v) A stochastic inventory control strategy was proposed
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