Inundation resilience analysis of metro-network from a complex system perspective using the grid hydrodynamic model and FBWM approach : a case study of Wuhan

The upward trend of metro flooding disasters inevitably brings new challenges to urban underground flood management. It is essential to evaluate the resilience of metro systems so that efficient flood disaster plans for preparation, emergency response, and timely mitigation may be developed. Traditional response solutions merged multiple sources of data and knowledge to support decision-making. An obvious drawback is that original data sources for evaluations are often stationary, inaccurate, and subjective, owing to the complexity and uncertainty of the metro station’s actual physical environment. Meanwhile, the flood propagation path inside the whole metro station network was prone to be neglected. This paper presents a comprehensive approach to analyzing the resilience of metro networks to solve these problems. Firstly, we designed a simplified weighted and directed metro network module containing six characteristics by a topological approach while considering the slope direction between sites. Subsequently, to estimate the devastating effects and details of the flood hazard on the metro system, a 100-year rainfall–flood scenario simulation was conducted using high-precision DEM and a grid hydrodynamic model to identify the initially above-ground inundated stations (nodes). We developed a dynamic node breakdown algorithm to calculate the inundation sequence of the nodes in the weighted and directed network of the metro. Finally, we analyzed the resilience of the metro network in terms of toughness strength and organization recovery capacity, respectively. The fuzzy best–worst method (FBWM) was developed to obtain the weight of each assessment metric and determine the toughness strength of each node and the entire network. The results were as follows. (1) A simplified three-dimensional metro network based on a complex system perspective was established through a topological approach to explore the resilience of urban subways. (2) A grid hydrodynamic model was developed to accurately and efficiently identify the initially flooded nodes, and a dynamic breakdown algorithm realistically performed the flooding process of the subway network. (3) The node toughness strength was obtained automatically by a nonlinear FBWM method under the constraint of the minimum error to sustain the resilience assessment of the metro network. The research has considerable implications for managing underground flooding and enhancing the resilience of the metro network

Application of Multicriteria Decision-Making Methods in Railway Engineering: A Case Study of Train Control Information Systems (TCIS)

In order to improve its position in the transport market railway, as a complex system, it has to fulfill a number of objectives such as increased capacity and asset utilization, improved reliability and safety, higher customer service levels, better energy efficiency and fewer emissions, along with increased economic viability and profits. Some of these objectives call for the implementation of maximum values, while some of them require minimum values. Additionally, some can be expressed quantitatively, while some, for example, customer service, can be described qualitatively through a descriptive scale of points. The application of MCDM in railway engineering can play a significant role. Therefore, the major objective of this chapter is the review of the application of MCDM methods in railway engineering. As one of the means in achieving the objectives of railways and above all the utilization of capacity are Train Control Information Systems (TCIS). Based on that, the aim of this chapter is the evaluation of the efficiency of TCIS in the improvement of railway capacity utilization through defined technical-technological indicators. The non-radial Data Envelopment Analysis (DEA) model for the evaluation of TCIS efficiency in improvement of utilization of railway capacity using the selected indicators is proposed. The proposed non-radial DEA model for TCIS efficiency evaluation in using railway capacity could be applied to an overall network or for separate parts of railway lines

Multi-Objective and Multi-Attribute Optimisation for Sustainable Development Decision Aiding

Optimization is considered as a decision-making process for getting the most out of available resources for the best attainable results. Many real-world problems are multi-objective or multi-attribute problems that naturally involve several competing objectives that need to be optimized simultaneously, while respecting some constraints or involving selection among feasible discrete alternatives. In this Reprint of the Special Issue, 19 research papers co-authored by 88 researchers from 14 different countries explore aspects of multi-objective or multi-attribute modeling and optimization in crisp or uncertain environments by suggesting multiple-attribute decision-making (MADM) and multi-objective decision-making (MODM) approaches. The papers elaborate upon the approaches of state-of-the-art case studies in selected areas of applications related to sustainable development decision aiding in engineering and management, including construction, transportation, infrastructure development, production, and organization management

Municipal solid waste management system: decision support through systems analysis

Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental EngineeringThe present study intends to show the development of systems analysis model applied to solid waste management system, applied into AMARSUL, a solid waste management system responsible for the management of municipal solid waste produced in Setúbal peninsula, Portugal. The model developed intended to promote sustainable decision making, covering the four columns: technical, environmental, economic and social aspects. To develop the model an intensive literature review have been conducted. To simplify the discussion, the spectrum of these systems engineering models and system assessment tools was divided into two broadly-based domains associated with fourteen categories although some of them may be intertwined with each other. The first domain comprises systems engineering models including cost-benefit analysis, forecasting analysis, simulation analysis, optimization analysis, and integrated modeling system whereas the second domain introduces system assessment tools including management information systems, scenario development, material flow analysis, life cycle assessment (LCA), risk assessment, environmental impact assessment, strategic environmental assessment, socio-economic assessment, and sustainable assessment. The literature performed have indicated that sustainable assessment models have been one of the most applied into solid waste management, being methods like LCA and optimization modeling (including multicriteria decision making(MCDM)) also important systems analysis methods. These were the methods (LCA and MCDM) applied to compose the system analysis model for solid waste. The life cycle assessment have been conducted based on ISO 14040 family of norms; for multicriteria decision making there is no procedure neither guidelines, being applied analytic hierarchy process (AHP) based Fuzzy Interval technique for order performance by similarity to ideal solution (TOPSIS). Multicriteria decision making have included several data from life cycle assessment to construct environmental, social and technical attributes, plus economic criteria obtained from collected data from stakeholders involved in the study. The results have shown that solutions including anaerobic digestion in mechanical biological treatment plant plus anaerobic digestion of biodegradable municipal waste from source separation, with energetic recovery of refuse derived fuel (RDF) and promoting pays-as-you-throw instrument to promote recycling targets compliance would be the best solutions to implement in AMARSUL system. The direct burning of high calorific fraction instead of RDF has not been advantageous considering all criteria, however, during LCA, the results were the reversal. Also it refers that aerobic mechanical biological treatment should be closed.Fundação para a Ciência e Tecnologia - SFRH/BD/27402/200

Hybrid SWARA-COPRAS method for risk assessment in deep foundation excavation project: an iranian case study

Existing risks in deep foundation excavation projects is a major issue in developing cities. With the rapid in-crease in the number of various deep foundation and excavation projects in big cities of Iran, many accidents related to deep excavation have been reported every year. These accidents affected delay and increased cost of project implemen-tation. Therefore identification and assessment of risks of these accidents is essential. The aim of the research was to develop a framework to overcome limitations of previous approaches to assess of risks in excavation projects. According to the complexity of a problem and the inherent uncertainty, the framework adopted SWARA (Step-wise Weight As-sessment Ratio Analysis) and COPRAS (COmplex PRoportional ASsessment) methods through introducing new criteria for risk assessment. Data was collected through interview, a literature review and a questionnaire survey distributed to excavation project experts. A case study of deep foundation excavation in Shiraz was presented. The results have shown that the risks involving construction safety, unfavourable geological conditions, shortage of managerial experience, in-complete emergency plan and subsidence of ground are the most significant risks excavation projects in Shiraz. The proposed framework and the obtained results can help stakeholders of excavation projects in developing countries better to manage project risks

Integrated Frameworks for Effective Multi-criteria Decision Making in Reliability Centred Maintenance of Industrial Machines

No abstract availabl

Studies on Risk and Occupational Health Hazards in Industrial Context: Some Case Research

This work articulates few case empirical studies on some aspects of risk management and occupational health hazards in the context of Indian Industries. Empirical research is research using empirical evidence. It is a way of gaining knowledge by means of direct and indirect observation or experience. The study focuses on five important domains investigating (i) the interrelationships among critical risk factors associated with software engineering project, (ii) risk management for IT outsourcing, (iii) risk management in metropolitan construction project, (iv) health hazard risk management, and (v) appropriate safety measure system selection for improving workers’ safety in an underground coal mining industry. In this research, an ISM approach has been applied to understand the significant interrelationships among the twenty three identified risk factors associated with the software engineering projects. In relation to IT outsourcing project, a hierarchical risk-breakdown structure has been proposed comprising sixty eight risk influencing factors under eleven risk dimensions. A case study has been conducted in a famous IT sector located at the eastern part of India. An improved fuzzy based decision making approach has been proposed for assessing overall IT outsourcing project risks. The degree of risk of identified risk factors have been shown in crisp values rather than the fuzzy numbers. A logical risk categorization framework has been proposed to categorize the risk factors into different risk levels. A unique action requirement plan has been suggested for effectively controlling the risks towards IT outsourcing project success. In the later part, total twenty one occupational health hazards have been identified and assessed their risk extent based on the exposure assessment procedure. Consequently, a constructive control measure plan has been suggested for different health hazards in view of their risk extent level. A novel risk-based decision making framework has been proposed for selecting the appropriate safety measure system in an underground coal mining industry. In addition to this, a case study has been conducted using twenty potential risk factors associated with five risk dimensions for assessing metropolitan construction project risks. Decision-makers’ risk bearing attitude has also been considered in this study. This study also explores the concept of risk matrix for categorizing the risk factors in different risk levels which would provide guidelines towards controlling risks for enhancing the overall project performance. Risk analysis models delignated herein have been case studied in relation to Indian industries. However, the model or hierarchy of various risk dimensions, risk sources; and classification of health hazards can be applicable to appropriate industries all over the globe. Some alteration may incur depending on the geographic situation of coal mining industry in analyzing occupational health hazards and associated risks. The framework for analyzing risks and occupational health hazards based on fuzzy based decision making approach can be applied in industrial context of different countries. Apart from the case studies mentioned above, the work also proposes a risk based decision support framework for selection of safety measure system for underground coal mines. In this case, occupational risks and alternative safety measure systems have been identified through literature survey. This part is a purely a theoretical formulation followed by analysis of assumed data which has not been case studied in reality. The novelty of the proposed framework is to analyze various risk dimensions in software engineering projects, IT Outsourcing, construction projects; also occupational health hazards in underground coal mining industry in a fuzzy based decision making framework. Instead of exploring historical data, survey report of the company; an experienced decision making group has been appointed to provide subjective judgement in regards of likelihood of occurrence and impact of various risks; consequence of exposure, period of exposure, and probability of exposure of various health hazards. Subjective decision making data have been transformed into appropriate fuzzy number sets to quantify overall risks extent. Thus, the proposed framework provides a platform to quantify extent of risk in industrial context

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems