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disasters
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Modeling and optimizing recovery strategies for power distribution system resilience
, Article IEEE Systems Journal ; Volume 15, Issue 4 , 2021 , Pages 4725-4734 ; 19328184 (ISSN) ; Fotuhi Firuzabad, M ; Moeini Aghtaie, M ; Safdarian, A ; Dehghanian, P ; Wang, F ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2021
Abstract
Both frequency and intensity of natural disasters have intensified in recent years. It is, therefore, essential to design effective strategies to minimize their catastrophic consequences. Optimizing recovery tasks, including distribution system reconfiguration (DSR) and repair sequence optimization (RSO), are the key to enhance the agility of disaster recovery. This article aims to develop a resilience-oriented DSR and RSO optimization model and a mechanism to quantify the recovery agility. In doing so, a new metric is developed to quantify the recovery agility and to identify the optimal resilience enhancement strategies. The metric is defined as 'the number of recovered customers divided...
The healthcare supply chain network design with traceability: A novel algorithm
, Article Computers and Industrial Engineering ; Volume 161 , 2021 ; 03608352 (ISSN) ; Akhavan Niaki, S. T ; Akhgar, M ; Ansari, M ; Sharif University of Technology
Elsevier Ltd
2021
Abstract
Both governments and health-related organizations must immediately act after a natural disaster happened, i.e., providing essential equipment and medicines to injured people as soon as possible and adequately. To achieve this goal, planning the distribution and the inventory of crucial items during a scenario of disasters, a relief supply chain network with four echelons, namely suppliers, warehouses, disaster locations, and medical centers, is designed. In this work, a bi-objective nonlinear mathematical model that follows two main concerns is proposed. First, we wish to minimize the supply chain costs in terms of both the traveling time between echelons and the inventory costs. Second, we...
Resiliency enhancement against wildfires
, Article 2021 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2021, 16 February 2021 through 18 February 2021 ; 2021 ; 9781728188973 (ISBN) ; Ghassemi, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2021
Abstract
The power system is the foundation for a modern society, and its safe and efficient operation is the prerequisite for our social and economic life. Manmade attacks and natural disasters such as hurricanes, tornadoes, floods, volcanic eruptions, and wildfires can cause temporary or permanent damages to the electric power system infrastructure. Wildfires are among the natural disasters rapidly growing in the last years. This has aroused growing attention toward the resiliency enhancement of power systems against wildfires. This paper reviews the activities developed to improve the resiliency of power systems, focusing on wildfires. In this regard, hardening and pre-event preparation,...
A novel privacy-preserved voluntary outage management model on a transactive energy scheme
, Article IET Generation, Transmission and Distribution ; Volume 16, Issue 17 , 2022 , Pages 3462-3472 ; 17518687 (ISSN) ; Koochaki, M ; Moeini Aghtaie, M ; Abbaspour, A ; Mazaheri, H ; Sharif University of Technology
John Wiley and Sons Inc
2022
Abstract
Unpredictable occurrence of natural disasters in modern power systems has significantly increased the attentions to the outage management of multi-microgrid (MMG) systems. In this regard, a multi-objective two-stage outage management scheme is presented in this paper to protect undamaged microgrids (MGs) against load curtailment and minimize the curtailed loads simultaneously. Considering the importance of power system economic, this scheme is designed in a privacy-preserved transactive energy (TE) market and enables all MGs to participate in outage management voluntarily. In detail, a DC optimization is autonomously operated in the first stage in each MG to supply its demand loads. Then,...
A Multi-Objective Robust Optimization Model for Logistics Planning in the Earthquake Response Phase [electronic resource]
, Article Transportation Research Part E: Logistics and Transportation Review, Elsevier ; Volume 49, Issue 1, January 2013, , Pages 217–249 ; Eshghi, Kourosh ; Dullaert, Wout ; Sharif University of Technology
Abstract
Usually, resources are short in supply when earthquakes occur. In such emergency situations, disaster relief organizations must use these scarce resources efficiently to achieve the best possible emergency relief. This paper therefore proposes a multi-objective, multi-mode, multi-commodity, and multi-period stochastic model to manage the logistics of both commodities and injured people in the earthquake response. Also, a robust approach is developed and used to make sure that the distribution plan performs well under the various situations that can follow an earthquake. Afterwards, it proposes a solution methodology according to hierarchical objective functions and uses it to illustrate the...
Location and distribution management of relief centers: A genetic algorithm approach
, Article International Journal of Information Technology and Decision Making ; Volume 14, Issue 4 , July , 2015 , Pages 769-803 ; 02196220 (ISSN) ; Farahani, R. Z ; De Brito, M. P ; Dullaert, W ; Sharif University of Technology
World Scientific Publishing Co. Pte Ltd
2015
Abstract
Humanitarian logistics is regarded as a key area for improved disaster management efficiency and effectiveness. In this study, a multi-objective integrated logistic model is proposed to locate disaster relief centers while taking into account network costs and responsiveness. Because this location problem is NP-hard, we present a genetic approach to solve the proposed model
A dynamic dispatching and routing model to plan/ re-plan logistics activities in response to an earthquake
, Article OR Spectrum ; 2013 , Pages 323-356 ; 01716468 (ISSN) ; Eshghi, K ; de Leeuw, S ; Sharif University of Technology
Abstract
The unpredictable nature and devastating impact of earthquakes enforce governments of disaster-prone regions to provide practical response plans to minimize damage and losses resulting from earthquakes. Logistics management is one of the key issues that should be considered for an appropriate response, in particular, the planning of the transport of commodities required during response and the evacuation of injured people. This paper develops a dynamic model for dispatching and routing vehicles in response to an earthquake. We focus on the transport of both commodity towards affected areas and injured people to hospitals. The proposed model is capable of receiving updated information at any...
A bi-level multi-objective location-routing optimization model for disaster relief operations considering public donations
, Article Socio-Economic Planning Sciences ; 2021 ; 00380121 (ISSN) ; Ghaebi Panah, M ; Mahdavi Amiri, N ; Shiripour, S ; Sharif University of Technology
Elsevier Ltd
2021
Abstract
In recent years, the number and severity of natural disasters occurring in various regions of the world have increased dramatically incurring heavy financial and human losses. Therefore, decision-makers have been concerned with ways of providing relief to reduce the losses. Here, we present a multi-objective bi-level model for disaster location-routing problem that provides the needed supplies through multiple suppliers, considering the supply risk. Moreover, to reduce the risk and increase efficiency, special attention is given to people's help for supplying goods having high priority and low risk. At the first level of the model, the cost and time objectives are considered, and at the...
Geo-spatiotemporal intelligence for smart agricultural and environmental eco-cyber-physical systems
, Article Studies in Computational Intelligence ; Volume 911 , 2021 , Pages 471-491 ; 1860949X (ISSN) ; Hemmati, O ; Baniardalan, F ; Farahmand, H ; Hajitabar, A ; Sharafi, S ; Aghajani, K ; Esmaeili, A ; Manzuri, M. T ; Sharif University of Technology
Springer Science and Business Media Deutschland GmbH
2021
Abstract
The rapid changes of the climate and the environment requires smart solutions and deployment of intelligent automated systems in agriculture and environment management. Rural communities should use artificial intelligence and big data analytics solutions in order to be able to mitigate the effects of climate change in the next decades. The Eco-Cyber-Physical-System (ecoCystem) is a combination of the living entities of the ecosystem in conjunction with the Cyber-Physical System (CPS) based components of the smart rural environments, interacting as a system. The goal of the ecoCystem is to use the power of artificial intelligence combined with Internet of Things (IOT) in order to provide...
Iran and COVID-19: A bottom-up, faith-driven, citizen-supported response
, Article Public Organization Review ; Volume 21, Issue 4 , 2021 , Pages 723-740 ; 15667170 (ISSN) ; Shahraini, S. M ; Yazdi, N ; Maleki, A ; Sharif University of Technology
Springer
2021
Abstract
The COVID-19 pandemic cast doubts on governments' traditional crisis responses and sparked a surge in citizen-led, participatory, bottom-up responses. Iran's experience is worth investigating because it relied significantly on citizen groups to manage the crisis despite long-term sanctions and extremely restricted resources. The authors undertook an exploratory case study using the grounded theory (GT) method and an online survey to explore Iran's confrontation. The central notion discovered was referred to as 'faith-driven civic engagement.’ The response was characterized by adaptability, promptness, and comprehensiveness. The causes and strategic orientations included intrinsic motives,...
Planning Before, and Emergency Response After, Disaster in Transportarion Networks
, Ph.D. Dissertation Sharif University of Technology ; Nasiri, Habibollah (Supervisor)
Abstract
Natural disasters claim major losses in human lives and belongings, as well as national infrastructures. Taking major earthquake as an example, the study has considered two sides of the problem, both before and after the incident. The former side is formulated as a multipartite optimization problem, in which each party’s activities are directed toward the long-term solution of the original problem. A heuristic method to solve the multipartite problem, and solve three example problems to show the applicability of the method was proposed. The solutions of example problems show that a directed problem solution reaches a better solution (in terms of the objective function value) than the...
A multi-objective robust optimization model for logistics planning in the earthquake response phase
, Article Transportation Research Part E: Logistics and Transportation Review ; Volume 49, Issue 1 , 2013 , Pages 217-249 ; 13665545 (ISSN) ; Eshghi, K ; Dullaert, W ; Sharif University of Technology
2013
Abstract
Usually, resources are short in supply when earthquakes occur. In such emergency situations, disaster relief organizations must use these scarce resources efficiently to achieve the best possible emergency relief. This paper therefore proposes a multi-objective, multi-mode, multi-commodity, and multi-period stochastic model to manage the logistics of both commodities and injured people in the earthquake response. Also, a robust approach is developed and used to make sure that the distribution plan performs well under the various situations that can follow an earthquake. Afterwards, it proposes a solution methodology according to hierarchical objective functions and uses it to illustrate the...
Flexibility analysis of a supply chain using design structure matrix
, Article Gain Competitive Advantage by Managing Complexity - Proceedings of the 14th International Dependency and Structure Modelling Conference, DSM 2012, 13 September 2012 through 14 September 2012 ; September , 2012 , Pages 79-88 ; 9783446433540 (ISBN) ; Malaek, S. M. B ; Emamipour, S ; Sharif University of Technology
Institution of Engineering Designers
2012
Abstract
Now days supply chain systems operate in an operational environment with high uncertainty. Customer globalization, increase of natural and manmade disasters, outsourcing in far distances have increased uncertainty. Flexibility as a capability can help systems included supply chains respond to uncertainty and deliver value to their users. auto supply chain is the one that has suffered from these disasters. This paper encapsulates operational environment uncertainty through scenario development, then scores the scenarios based on some proxies. Design structure matrix is proposed to show the typical auto supply chain relationships before scenario occurring consequences and after that. in the...
Optimal path-planning for mobile robots to find a hidden target in an unknown environment based on machine learning
, Article Journal of Ambient Intelligence and Humanized Computing ; 2018 , Pages 1-10 ; 18685137 (ISSN) ; Rasooli, A ; Khodaygan, S ; Sharif University of Technology
Springer Verlag
2018
Abstract
Using mobile robots in disaster areas can reduce risks and the search time in urban search and rescue operations. Optimal path-planning for mobile robotics can play a key role in the reduction of the search time for rescuing victims. In order to minimize the search time, the shortest path to the target should be determined. In this paper, a new integrated Reinforcement Learning—based method is proposed to search and find a hidden target in an unknown environment in the minimum time. The proposed algorithm is developed in two main phases. Depending on whether or not the mobile robot receives the signal from the hidden target, phases I or II of the proposed algorithm can be carried out. Then,...
Hardening strategy to boost resilience of distribution systems via harnessing a proactive operation model
, Article 2019 Smart Gird Conference, SGC 2019, 18 December 2019 through 19 December 2019 ; 2019 ; 9781728158945 (ISBN) ; Jalilian, A ; Safdarian, A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
Nowadays, large-scale power outages induced by ever-growing natural disasters are increasing at a galloping rate. In this regard, this paper aims at improving the resilience of power distribution systems in facing high impact low probability (HILP) events in the planning phase of the system. To this end, optimal switch placement along with the optimal distribution line hardening strategies is proposed to mitigate the repercussions of the natural calamities. So, decreasing the failure probability of the distribution lines alongside the optimal placement of remote-controlled switches (RCSs) to increase the maneuvering capability of the system, the system operator would be able to strengthen...
Optimal distribution of the injured in a multi-type transportation network with damage-dependent travel times: Two metaheuristic approaches
, Article Socio-Economic Planning Sciences ; Volume 68 , 2019 ; 00380121 (ISSN) ; Mahdavi Amiri, N ; Sharif University of Technology
Elsevier Ltd
2019
Abstract
We study a location-allocation-routing problem for distribution of the injured in a disaster response scenario, considering a three-type transportation network with separate links. A circle-based approach to estimate the impacts of the disaster is presented. After formulating relations for computing the percentage of the injured, the destruction percentage and the damage-dependent travel times, the problem is formulated as an integer nonlinear program. We utilize a genetic algorithm and a discrete version of the imperialist competitive algorithm for solving large problems. An empirical study focused on earthquakes in Tabriz, Iran, illustrates applicability of the proposed model and...
Optimal path-planning for mobile robots to find a hidden target in an unknown environment based on machine learning
, Article Journal of Ambient Intelligence and Humanized Computing ; Volume 10, Issue 5 , 2019 , Pages 1841-1850 ; 18685137 (ISSN) ; Rasooli, A ; Khodaygan, S ; Sharif University of Technology
Springer Verlag
2019
Abstract
Using mobile robots in disaster areas can reduce risks and the search time in urban search and rescue operations. Optimal path-planning for mobile robotics can play a key role in the reduction of the search time for rescuing victims. In order to minimize the search time, the shortest path to the target should be determined. In this paper, a new integrated Reinforcement Learning—based method is proposed to search and find a hidden target in an unknown environment in the minimum time. The proposed algorithm is developed in two main phases. Depending on whether or not the mobile robot receives the signal from the hidden target, phases I or II of the proposed algorithm can be carried out. Then,...
Multi-step island formation and repair dispatch reinforced by mutual assistance after natural disasters
, Article International Journal of Electrical Power and Energy Systems ; Volume 126 , 2021 ; 01420615 (ISSN) ; Vakilian, M ; Farzin, H ; Lehtonen, M ; Sharif University of Technology
Elsevier Ltd
2021
Abstract
Extreme weather events can devastate parts of power grids. Thus, the appropriate post-disaster reaction is a crucial duty for power utilities. To address this important concern, a new two-stage framework is proposed in this paper. Stage I optimally coordinates disaster mutual assistance between affected and supporting utilities. To this end, distance between the damaged and supporting utilities, extent of damage, and repair resources are taken into consideration as decision criteria. Then, a novel formulation in the form of mixed integer linear programming (MILP) is developed for mutual aid management problem. The results of stage I are used as inputs to stage II. A new multi-horizon...
A stochastic framework for optimal island formation during two-phase natural disasters
, Article IEEE Systems Journal ; 2021 ; 19328184 (ISSN) ; Vakilian, M ; Farzin, H ; Lehtonen, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2021
Abstract
This article proposes a new three-stage stochastic framework for dealing with predictable two-phase natural disasters in distribution systems. This framework is a multiobjective optimization, in which the amount of curtailed energy, the number of switching actions, and the vulnerability of operational components are selected as the main criteria for decision-making process. The optimization problem is formulated in the form of a stochastic mixed-integer linear programming (MILP) problem. In this article, a windstorm event followed by flooding is analyzed as a two-phase natural disaster. In this regard, the uncertainties associated with gust-wind speed, floodwater depths, and load demands are...
Tie-line planning for resilience enhancement in unbalanced distribution networks
, Article IET Generation, Transmission and Distribution ; 2021 ; 17518687 (ISSN) ; Safdarian, A ; Sharif University of Technology
John Wiley and Sons Inc
2021
Abstract
Over the past decades, there has been a dramatic increase in the frequency of natural disasters, which are the leading causes of large-scale power outages. This paper, therefore, assesses the significance and role of optimal tie-line construction in improving the service restoration performance of unbalanced power distribution systems in the aftermath of high-impact low-probability incidents. In doing so, a restoration process aware stochastic mixed-integer linear programming model is developed to find the optimal locations for new tie-line construction in unbalanced three-phase distribution systems. In particular, the restoration process of distribution systems, including the fault...