Current Application Fields of ELECTRE and PROMETHEE: A Literature Review

Multi-criteria decision making techniques are widely used today. In this study, it was examined the current usage areas of ELECTRE and PROMETHEE, which are in the class of outranking-based multiple criteria decision techniques, in Turkey and the world. In this regard, the studies carried out in 2016 and the first four months of 2017 were scanned with the help of Google Scholar. Thus, it is aimed to put forward the latest state of development of ELECTRE and PROMETHEE, and to give an idea about their future application forms and fields. As a result, it was seen that application problems of ELECTRE and PROMETHEE in various fields was tried to remove, and designed appropriate methods for special cases in studies. Furthermore, evaluation according to scenario variations, solving complex decision problems with metaheuristics, common usage of hesitant fuzzy implementations, proliferation of group decision preference, increasing the number of applications of hybrid techniques, used softwares, sensitivity analyses, two linguistic approaches taking an important place in fuzzification have been identified as remarkable results

Fecal glucocorticoids reflect socio-ecological and anthropogenic stressors in the lives of wild spotted hyenas

Our aim was to identify natural and anthropogenic influences on the stress physiology of large African carnivores, using wild spotted hyenas (Crocuta crocuta) as model animals. With both longitudinal data from a single social group, and cross-sectional data from multiple groups, we used fecal glucocorticoids (fGC) to examine potential stressors among spotted hyenas. Longitudinal data from adult members of a group living on the edge of the Masai Mara National Reserve, Kenya, revealed that fGC concentrations were elevated during two periods of social upheaval among adults, especially among younger females; however, prey availability, rainfall, and presence of lions did not influence fGC concentrations among hyenas. Our results suggested that anthropogenic disturbance in the form of pastoralist activity, but not tourism, influenced fGC concentrations among adult male hyenas; rising concentrations of fGC among males over 12 years were significantly correlated with increasing human population density along the edge of the group\u27s home range. As hyenas from this social group were frequently exposed to anthropogenic disturbance, we compared fGC concentrations among these hyenas with those obtained concurrently from hyenas living in three other groups undisturbed by pastoralist activity. We found that fGC concentrations from the undisturbed groups were significantly lower than those in the disturbed group, and we were able to rule out tourism and ecological stressors as sources of variation in fGC among the populations. Thus it appears that both social instability and anthropogenic disturbance, but not the ecological variables examined, elevate fGC concentrations and represent stressors for wild spotted hyenas. Further work will be necessary to determine whether interpopulation variation in stress physiology predicts population decline in groups exposed to intensive anthropogenic disturbance

A fuzzy decision tool to evaluate the sustainable performance of suppliers in an agrifood value chain

Sustainable supply chain management has received much attention from both academia and industry due to various issues such as economic stability, environment conservation, and social ethics. To improve the sustainable performance of a value chain, its members need to carefully select their suppliers in relation to their own strategy. Thus, an effective tool for sustainable supplier selection and evaluation is essential, which considers the triple bottom line (TBL) of economic, environmental and social aspects by means of criteria adapted to the situation analysed. This paper develops a fuzzy decision tool to evaluate the sustainable performance of suppliers according to TBL. Sustainability criteria are identified to take into account the real hotspots in a food value chain. The proposed model integrates triangular fuzzy numbers (TFN), AHP (Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) in a novel way to consider quantitative and qualitative criteria as well as objective and subjective data. This is missing in most existing research when building their fuzzy models for supplier selection, but critical in dealing with the heterogeneous data available for TBL assessment. The application in a sustainable agrifood value chain illustrates the effectiveness of the proposed tool

A Modified FMEA Approach to Enhance Reliability of Lean Systems

Purpose - The purpose of this thesis is to encourage the integration of Lean principles with reliability models to sustain Lean efforts on long term basis. This thesis presents a modified FMEA that will allow Lean practitioners to understand and improve the reliability of Lean systems. The modified FMEA approach is developed based on the four critical resources required to sustain Lean systems: personnel, equipment, material and schedule. Design/methodology/approach – A three phased methodology approach is presented to enhance the reliability of Lean systems. The first phase compares actual business and operational conditions with conditions assumed in Lean implementation. The second phase maps potential deviations of business and operational conditions to their root cause. The third phase utilizes a modified Failure Mode and Effects Analysis (FMEA) to prioritize issues that the organization must address. Findings – A literature search shows that practical methodologies to improve the reliability of Lean systems are non existent. Research Limitations/Implications –The knowledge database involves tedious calculations and hence it needs to be automated. Originality/Value • Defined Lean system reliability • Developed conceptual model to enhance the Lean system reliability • Developed knowledge base in the form of detailed hierarchical root trees for the four critical resources that support our Lean system reliability • Developed Risk Assessment Value (RAV) based on the concept of effectiveness of detection using Lean controls when Lean designer implements Lean change. • Developed modified FMEA for the four critical resources • Developed RPLS tool to prioritize Lean failures • Developed case study to analyze RPN and RAV approac

Managing Highway Bridges against Climate-Triggered Extreme Events in Cold Regions

Highway bridges represent a significant investment by Governments at both Provincial and Federal levels and their importance is underscored by the fact that every citizen derives a benefit, directly or indirectly, from public transportation infrastructure. As with any engineering product, highway bridges must be well designed and robust to avoid any malfunction that could jeopardise the lives of people. Further, highway bridges deteriorate over time and need preservation intervention applied at suitable intervals over the bridge’s service life. Determining the timing and order of implementation of preservation work among deficient bridges in a highway bridge inventory is an important function of bridge management. The doctoral research reported in this thesis aimed to devise a method for the resilience/vulnerability rating of highway bridges against climate-triggered extreme events/ loads. The research also sought to devise a ranking technique for bridge projects’ programming by pursuing a one-directional, non-iterative, method that could maximize the value function and significantly cut down the computer run time for the ranking analysis. The research outcomes include a weighted-criteria method for the multi-criteria ranking, a practical tool for the resilience/vulnerability rating of highway bridges against extreme events such as deck flooding and abutment washout, and a method for determining the magnitude of climate-triggered extreme load (e.g. ice accretion, pier scour) that could potentially cause bridge failure. The projects’ ranking method developed in this research, including the development of a weighted criteria formulation, could potentially be adopted by bridge management systems in North America and elsewhere. Further, it is expected that the method will influence future development of multi-criteria ranking in bridge management and other fields. Similarly, the proposed new method for climate change resilience rating of highway bridges is a significant effort at translating the general scientific and engineering impacts’ discussion of climate change into an engineering tool for the continuous management of bridges. Finally, it will be important for transportation agencies to determine beforehand what magnitude of climate-triggered extreme load would produce bridge distress and potential failure, and this thesis provides a solution to that problem

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