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

Efficiency of the rail sections in Brazilian railway system, using TOPSIS and a genetic algorithm to analyse optimized scenarios

A railway system plays a significant role in countries with large territorial dimensions. The Brazilian rail cargo system (BRCS), however, is focused on solid bulk for export. This paper investigates the extreme performances of BRCS through a new hybrid model that combines TOPSIS with a genetic algorithm for estimating the weights in optimized scenarios. In a second stage, the significance of selected variables was assessed. The transport of any type of cargo, a centralized control of the operation, and sharing the railway track pushing competition, and the diversification of services are significant for high performance. Public strategies are discussed.Indisponível

Strategies for sustainable socio-economic development and mechanisms their implementation in the global dimension

The authors of the book have come to the conclusion that it is necessary to effectively use modern approaches to developing and implementation strategies of sustainable socio-economic development in order to increase efficiency and competitiveness of economic entities. Basic research focuses on economic diagnostics of socio-economic potential and financial results of economic entities, transition period in the economy of individual countries and ensuring their competitiveness, assessment of educational processes and knowledge management. The research results have been implemented in the different models and strategies of supply and logistics management, development of non-profit organizations, competitiveness of tourism and transport, financing strategies for small and medium-sized enterprises, cross-border cooperation. The results of the study can be used in decision-making at the level the economic entities in different areas of activity and organizational-legal forms of ownership, ministries and departments that promote of development the economic entities on the basis of models and strategies for sustainable socio-economic development. The results can also be used by students and young scientists in modern concepts and mechanisms for management of sustainable socio-economic development of economic entities in the condition of global economic transformations and challenges

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

An Integrated Risk-Based Asset Management Framework for Subway Systems

Subway systems play a vital role connecting thousands of people to different destinations on a daily basis. The Canadian infrastructure report card recommended encouraging infrastructure owners to establish asset-management plans based on rates of deterioration and community service levels. Moreover, the 2013 report card for America’s infrastructure assigned a grade D to transit systems indicating they are in a poor condition with strong risk of failure. A possible solution proposed by the 2013 report card is adopting a comprehensive asset management system to maximize investments in light of the fund scarcity dilemma. The main objective of this research is to develop a risk-based asset management framework for subway networks. The framework works along three interrelated sub-models followed by two main models. A generic subway hierarchy is proposed and risk is assessed using three sub-models; probability of failure, consequences of failure and criticality index. Probability of failure is predicted for different structural elements using inspection reports and Weibull reliability function. Consequences of failure are assessed based on seven criteria along financial, social, and, operational perspectives. A criticality index is introduced to the classical risk equation to assess the functional importance of a station in its location using seven attributes along three main criteria. The Fuzzy Analytical Network Process is employed to analyze experts’ feedback used in the consequences of failure and criticality sub-models. This insures incorporating interdependency between criteria and fuzziness of the analysis. The three sub-models are used as inputs in a fuzzy inference engine to compute the predicted risk index. A set of thirty rules derived from experts through interviews and questionnaires is used to shape the relation between the fuzzy output and input variables. Finally, the second model is developed for a risk-based budget allocation model. The model utilizes the risk index components as objective functions. Decision variables are identified as five generic rehabilitation actions along their cost, time, and percentage improvement. The model provides the recommended rehabilitation action in light of the network total risk index and the available budget per time span. This is the first risk assessment framework proposed in the subway networks domain. Using a network analysis approach, the elements of a risk index are analyzed and aggregated from elements to lines and segments levels. The model revealed probability of failure to be the main driver of a risk index followed by criticality index and last, consequences of failure. Within the expected consequences of failure, social impacts had the highest impact (38%) based on experts’ feedback. The criticality index sub-model revealed station location to be the most important criteria (35%) followed by station nature of use (33%) and finally, station characteristics (32%). A segment of six stations from Montreal subway network is analyzed. The assessment indicates two stations with high risk indices showing the necessity of an intervention action. The budget allocation model prioritizes stations for rehabilitation according to the decision maker’s risk appetite, assumed at 0.6. The revised risk index for STA 4 dropped from 0.821 to 0.521 and the overall segment index dropped to zero. This research presents a basis for evaluating subway infrastructure on a structural and functional basis. It assists authorities to derive an informed rehabilitation decision using a generic and consistent framework. The heuristic decision making process followed by authorities is translated into a detailed framework that can be easily implemented and updated. The presented outline can be equally used for segments or the entire network

An Integrated Risk-Based Asset Management Framework for Subway Systems

Subway systems play a vital role connecting thousands of people to different destinations on a daily basis. The Canadian infrastructure report card recommended encouraging infrastructure owners to establish asset-management plans based on rates of deterioration and community service levels. Moreover, the 2013 report card for America’s infrastructure assigned a grade D to transit systems indicating they are in a poor condition with strong risk of failure. A possible solution proposed by the 2013 report card is adopting a comprehensive asset management system to maximize investments in light of the fund scarcity dilemma. The main objective of this research is to develop a risk-based asset management framework for subway networks. The framework works along three interrelated sub-models followed by two main models. A generic subway hierarchy is proposed and risk is assessed using three sub-models; probability of failure, consequences of failure and criticality index. Probability of failure is predicted for different structural elements using inspection reports and Weibull reliability function. Consequences of failure are assessed based on seven criteria along financial, social, and, operational perspectives. A criticality index is introduced to the classical risk equation to assess the functional importance of a station in its location using seven attributes along three main criteria. The Fuzzy Analytical Network Process is employed to analyze experts’ feedback used in the consequences of failure and criticality sub-models. This insures incorporating interdependency between criteria and fuzziness of the analysis. The three sub-models are used as inputs in a fuzzy inference engine to compute the predicted risk index. A set of thirty rules derived from experts through interviews and questionnaires is used to shape the relation between the fuzzy output and input variables. Finally, the second model is developed for a risk-based budget allocation model. The model utilizes the risk index components as objective functions. Decision variables are identified as five generic rehabilitation actions along their cost, time, and percentage improvement. The model provides the recommended rehabilitation action in light of the network total risk index and the available budget per time span. This is the first risk assessment framework proposed in the subway networks domain. Using a network analysis approach, the elements of a risk index are analyzed and aggregated from elements to lines and segments levels. The model revealed probability of failure to be the main driver of a risk index followed by criticality index and last, consequences of failure. Within the expected consequences of failure, social impacts had the highest impact (38%) based on experts’ feedback. The criticality index sub-model revealed station location to be the most important criteria (35%) followed by station nature of use (33%) and finally, station characteristics (32%). A segment of six stations from Montreal subway network is analyzed. The assessment indicates two stations with high risk indices showing the necessity of an intervention action. The budget allocation model prioritizes stations for rehabilitation according to the decision maker’s risk appetite, assumed at 0.6. The revised risk index for STA 4 dropped from 0.821 to 0.521 and the overall segment index dropped to zero. This research presents a basis for evaluating subway infrastructure on a structural and functional basis. It assists authorities to derive an informed rehabilitation decision using a generic and consistent framework. The heuristic decision making process followed by authorities is translated into a detailed framework that can be easily implemented and updated. The presented outline can be equally used for segments or the entire network

An Integrated Risk-Based Asset Management Framework for Subway Systems

Subway systems play a vital role connecting thousands of people to different destinations on a daily basis. The Canadian infrastructure report card recommended encouraging infrastructure owners to establish asset-management plans based on rates of deterioration and community service levels. Moreover, the 2013 report card for America’s infrastructure assigned a grade D to transit systems indicating they are in a poor condition with strong risk of failure. A possible solution proposed by the 2013 report card is adopting a comprehensive asset management system to maximize investments in light of the fund scarcity dilemma. The main objective of this research is to develop a risk-based asset management framework for subway networks. The framework works along three interrelated sub-models followed by two main models. A generic subway hierarchy is proposed and risk is assessed using three sub-models; probability of failure, consequences of failure and criticality index. Probability of failure is predicted for different structural elements using inspection reports and Weibull reliability function. Consequences of failure are assessed based on seven criteria along financial, social, and, operational perspectives. A criticality index is introduced to the classical risk equation to assess the functional importance of a station in its location using seven attributes along three main criteria. The Fuzzy Analytical Network Process is employed to analyze experts’ feedback used in the consequences of failure and criticality sub-models. This insures incorporating interdependency between criteria and fuzziness of the analysis. The three sub-models are used as inputs in a fuzzy inference engine to compute the predicted risk index. A set of thirty rules derived from experts through interviews and questionnaires is used to shape the relation between the fuzzy output and input variables. Finally, the second model is developed for a risk-based budget allocation model. The model utilizes the risk index components as objective functions. Decision variables are identified as five generic rehabilitation actions along their cost, time, and percentage improvement. The model provides the recommended rehabilitation action in light of the network total risk index and the available budget per time span. This is the first risk assessment framework proposed in the subway networks domain. Using a network analysis approach, the elements of a risk index are analyzed and aggregated from elements to lines and segments levels. The model revealed probability of failure to be the main driver of a risk index followed by criticality index and last, consequences of failure. Within the expected consequences of failure, social impacts had the highest impact (38%) based on experts’ feedback. The criticality index sub-model revealed station location to be the most important criteria (35%) followed by station nature of use (33%) and finally, station characteristics (32%). A segment of six stations from Montreal subway network is analyzed. The assessment indicates two stations with high risk indices showing the necessity of an intervention action. The budget allocation model prioritizes stations for rehabilitation according to the decision maker’s risk appetite, assumed at 0.6. The revised risk index for STA 4 dropped from 0.821 to 0.521 and the overall segment index dropped to zero. This research presents a basis for evaluating subway infrastructure on a structural and functional basis. It assists authorities to derive an informed rehabilitation decision using a generic and consistent framework. The heuristic decision making process followed by authorities is translated into a detailed framework that can be easily implemented and updated. The presented outline can be equally used for segments or the entire network