An evolutionary multi-objective optimization approach to disaster waste management: A case study of Istanbul, Turkey

Onan, Kıvanç; Ülengin, Füsun; Şennaroğlu, Bahar

doi:10.1016/j.eswa.2015.07.039

Cited by 58 publications

(40 citation statements)

References 53 publications

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“…When separate fire safety issues combined, there will also arise interactions. For example, in the determination of escape routes, the lack of sprinkler in the building is an important parameter [1,2]. Human behaviour is also a very important factor concerning the fire safety.…”

Section: Introductionmentioning

confidence: 99%

A multi-objective route planning model based on genetic algorithm for cuboid surfaces

2018

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During a natural disaster, risk management for the evacuation of people in high-rise buildings is very important for saving lives. In the case of fire, all parameters such as detection, lighting, warning systems, etc. for safety must be used interactively. Determination of evacuation conditions and different ways out are important parameters during the fire. In this study, a system is proposed for evacuating people from building with the shortest/safest route, taking into account certain factors to evaluate the current situation of the fire. Travelling Salesman Problem (TSP) may be adapted to this real-life problem to protect people in the shortest time finding optimum route. In this study, the system based on Genetic Algorithm is performed using the online information about smoke, heat and safety level, the location of fire and the potential congestion of people in order to evacuate people from the building with safety route. The system contains two-and three-dimensional surface applications to ensure evacuation with optimum distance inside/outside of the building. Results are evaluated considering the evacuation distance. Compared to other methods in the literature, the solution to this problem is improved by adding the evacuation process for the elevator and inside of the building.

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Section: Introductionmentioning

confidence: 99%

A multi-objective route planning model based on genetic algorithm for cuboid surfaces

2018

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“…In a study related to the evaluation of disaster waste management, Crowley (2017) surveyed the effectiveness and efficiency of pre-disaster debris management planning in several counties in the U.S. Pramudita et al (2014) discussed the methods of construction of a transportation network for disaster debris if a Tokyo inland earthquake were to happen. Onan et al (2015) created a decision-making tool to estimate disaster waste amount and investigate transportation networks and the location of temporary storage sites. Cheng and Thompson (2016) conducted a land suitability analysis to select candidate temporary disaster waste management sites that provide storing, chipping, burning, and sorting for reduction, reuse, and recycling.…”

Section: Introductionmentioning

confidence: 99%

Life cycle assessment and life cycle costs for pre-disaster waste management systems

et al. 2017

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This study develops a method of environmental and economic evaluation of an integrated disaster waste management system that considers the spatial scale of removal, transport, and treatment of disaster waste. A case study was conducted on combustibles, which is a type of disaster waste derived from dwellings, in Mie Prefecture, Japan. First, we calculated the quantity and the spatial distribution of disaster waste derived from dwellings and tsunami debris produced as a result of a large-scale earthquake. The quantity of disaster waste was estimated as 7,178,000t with functioning flood-preventing facilities and 11,956,000t without functioning flood prevention facilities. Ensuring resilience in the face of earthquakes and tsunamis by renovating flood-preventing facilities is extremely important in decreasing the production of wastes, especially in coastal regions. Next, the transportation network for transporting combustibles in disaster waste to temporary storage sites, incineration plants, and landfill was constructed using an optimization model. The results showed that if flood-preventing facilities do not function properly, the installation of temporary incineration facilities becomes essential. Life-cycle emissions of CO, SO, NO, and PM and the costs of removal, storage, and treatment of combustibles were calculated as 258,000t, 618t, 1705t, 7.9t, and 246millionUSD, respectively, in the case of functioning flood-preventing facilities. If flood-preventing facilities do not function, the quantity of environmentally unfriendly emissions and the costs increase. This result suggested the significance of renovation in order to maintain the conditions of flood-preventing facilities to decrease the environmental burden and costs as well as keep the production of disaster waste at a minimum.

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“…The first research work was done by Onan et al [24] in which a framework for determining the location of a temporary disaster debris management site was proposed. With the objective of minimizing the cost and risk of hazardous waste exposure, they considered the factors of planning for the collection and transportation of disaster waste.…”

Section: Literature Reviewmentioning

confidence: 99%

An Integrated Location-Allocation Model for Temporary Disaster Debris Management under an Uncertain Environment

Habib

Sarkar

2017

Sustainability

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Natural disasters always generate an overwhelming amount of debris. Reusing and recycling waste from disasters are essential for sustainable debris management. Before recycling the debris, it is necessary to sort this mixed waste. To perform the sorting process efficiently, a Temporary Disaster Debris Management Site (TDDMS) is required, and the selection of TDDMS is a multi-criteria decision-making problem due to its numerous regional and municipal constraints. This paper provides a two-phase framework for sustainable debris management during the response phase of disasters. In the first phase, a methodology for TDDMS selection is proposed that consists of Analytical Network Process (ANP) and a fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In the second phase, a debris allocation optimization model is developed to allocate the debris from disaster-affected regions to the selected TDDMS. A city prone to hurricane damage is selected to illustrate the proposed framework. For the debris allocation purpose, five TDDMS are chosen, among which three sites are selected using the proposed methodology. To illustrate the utilization of the proposed study, a numerical example with two different scenarios is provided. Numerical outcomes prove that the model results in a sustainable debris management system for disasters.

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An evolutionary multi-objective optimization approach to disaster waste management: A case study of Istanbul, Turkey

Cited by 58 publications

References 53 publications

A multi-objective route planning model based on genetic algorithm for cuboid surfaces

A multi-objective route planning model based on genetic algorithm for cuboid surfaces

Life cycle assessment and life cycle costs for pre-disaster waste management systems

An Integrated Location-Allocation Model for Temporary Disaster Debris Management under an Uncertain Environment

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