Multicriteria ranking using weights which minimize the score range

Various schemes have been proposed for generating a set of non-subjective weights when aggregating multiple criteria for the purposes of ranking or selecting alternatives. The maximin approach chooses the weights which maximise the lowest score (assuming there is an upper bound to scores). This is equivalent to finding the weights which minimize the maximum deviation, or range, between the worst and best scores (minimax). At first glance this seems to be an equitable way of apportioning weight, and the Rawlsian theory of justice has been cited in its support.We draw a distinction between using the maximin rule for the purpose of assessing performance, and using it for allocating resources amongst the alternatives. We demonstrate that it has a number of drawbacks which make it inappropriate for the assessment of performance. Specifically, it is tantamount to allowing the worst performers to decide the worth of the criteria so as to maximise their overall score. Furthermore, when making a selection from a list of alternatives, the final choice is highly sensitive to the removal or inclusion of alternatives whose performance is so poor that they are clearly irrelevant to the choice at hand

Evaluating the efficiencies of alternative energy resources for electricity generation in Turkey

Birden çok girdi ve çıktıya sahip karar birimlerinin göreli performanslarının ölçülmesi için kullanılan klasik Veri Zarflama Analizi (VZA) modellerinde yalnızca kesin sayısal veriler kullanılabilir. Oysa gerçek hayattaki birçok uygulamada karar birimlerinin kullanıldığı girdiler ve ürettiği çıktılar belirsiz, aralıklar halinde veya sözel olarak ifade edilmiş olabilir. Enerji kaynak alternatiflerinin etkinlik analizindeki uzman görüşleri sözel olarak, maliyet girdisi de belirsiz olduğu için bulanık sayılarla ifade edilmektedir. Bu çalışmada, Türkiye’de elektrik üretimi için kullanılabilecek enerji kaynak alternatiflerinin etkinliğinin ölçülmesi için Bulanık VZA (BVZA) kullanılmıştır. Makalede, Charnes vd. (1978) tarafından geliştirilen klasik VZA modelinin (CCR modeli) dual formunu temel alan yeni bir bulanık VZA formülasyonu (Dual Bulanık Veri Zarflama analizi–DBVZA) önerilmektedir. Bulanık model, α-kesmeleri yaklaşımı kullanılarak doğrusallaştırılmıştır. DBVZA modelinde, diğer bulanık VZA modellerinden farklı olarak, Karar Birimlerinin (KB) etkinliği ölçülürken, bulanık girdi ve çıktı değerlerinin α-kesmelerinin uç noktaları yerine, tüm α-kesmeleri performans ölçümünde kullanılmakta ve böylelikle aralığın içindeki verilerin de etkinlik analizinde dikkate alınması sağlanmaktadır. DBVZA’nın karar vericilere sağladığı bir diğer avantaj, tüm α seviyelerinde etkinlik sınırında yer alan, bir başka deyişle %100 etkin olan KB sayısının diğer bulanık VZA yöntemlerine göre düşük olmasıdır. Bu durum KB’lerin etkinliklerine göre sıralanmasını kolaylaştırmaktadır. Ayrıca DBVZA ile yapılan uygulamalarda karar birimlerinin etkinliklerine göre sıralanabilmesi için herhangi bir bulanık sıralama yöntemine ihtiyaç duyulmamaktadır. Anahtar Kelimeler: Veri zarflama analizi, bulanık matematik programlama, etkinlik analizi, enerji alternatifleri, elektrik üretimi.With the beginning of 21st century, the consumption of energy all over the world is increasing far more rapidly than in the last century. Today, energy is the most important basic input for economical and industrial development. Especially for developing countries like Turkey, alternative energy resources for power plants have very high strategic importance. In Turkey, like many other countries, the generation of electric power is based on fossil fuels. The volatility of oil prices, the exhaustibility of fossil fuels and environmental issues force developing industries to revise their alternatives for electricity generation. Now, it is the time to give more attention to stable, reliable and non-polluting energy resources. Most forms of alternative energy resources are dependent on geographical and environmental factors which vary from country to country. Every country has to determine its energy policy considering its specific conditions like demand and supply equilibrium, dependency on other countries, geographical conditions, variations of population, etc.Turkey is a country that lacks sufficient conventional energy resources and is importing oil and natural gas from other countries. As an emerging country, Turkey has been one of the fastest growing energy markets in the world. Turkey's share in total OECD production is expected to increase from 2% in 1995 to 7% in 2020s, making Turkey a significant economic power within the OECD countries but this will be possible only with a proper energy policy and efficient selection of alternative energy resources. Selecting among different resource alternatives is a very difficult task as the factors which affect the efficiency of energy resources are imprecise and require expert knowledge. The criteria, such as sustainability, security etc. are defined in linguistic form as it is impossible to quantify them. As a result, some of the criteria of efficiency have to be introduced in analysis as fuzzy data. The performance assessment methods which enable us to use fuzzy inputs and outputs are suitable for the evaluation of energy alternatives efficiencies. The potentially viable electricity resources considered for Turkey are oil, coal, natural gas, nuclear power, hydropower, wind power, solar power and biomass power. For the evaluation criteria of these energy resources and their values, we refer to expert opinions. The details about efficiency criteria and results of the analysis can be found in the application. The energy resources are ranked by their efficiency scores as follows: Wind, natural gas, hydropower, biomass, coal, oil, solar power and nuclear power. The existing data envelopment analysis (DEA) models for measuring the relative efficiencies of a set of decision making units (DMUs) using various inputs to produce various outputs are limited to crisp data.  However, the data acquired from expert opinions for evaluating the efficiencies of alternative energy resources is generally in linguistic form. This paper proposes a fuzzy DEA formulation based on dual form of the DEA model developed by Charnes et al. (1978) to deal with imprecise or linguistic data that we frequently come across in real-world applications. The model is transformed into a family of crisp linear problems using the "-cut approach. In dual fuzzy DEA formulation, the entire "-cut interval is taken into account unlike many other fuzzy DEA formulations which use the boundary points of "-cuts when calculating the efficiency scores of DMUs. Dual fuzzy DEA is suitable to rank every DMU in all "-levels as we are not faced with the problem of having too many DMUs on the efficient frontier. Another advantage of the dual fuzzy DEA formulation is that, it does not require any fuzzy ranking method to rank the DMUs. As the result, dual fuzzy DEA can be very useful in performance evaluation, especially when decision makers or researchers have few DMUs and a large number of decision criteria (inputs and outputs) as they will be able to rank all DMUs according their efficiency scores. The paper is organized as follows: A literature survey of fuzzy DEA models is followed by the presentation of the classical DEA model (CCR formulation), dual form of the CCR formulation and fuzzy DEA model. Then, the linearization of dual fuzzy DEA by ?-cut approach and variable alterations is introduced. After a real life application concerning the assessment of energy alternatives for electricity production in Turkey, the paper ends with the conclusion. Keywords: Data envelopment analysis, fuzzy mathematical programming, efficiency analysis, energy alternatives, electricity generation

Fit between humanitarian professionals and project requirements: hybrid group decision procedure to reduce uncertainty in decision-making

Choosing the right professional that has to meet indeterminate requirements is a critical aspect in humanitarian development and implementation projects. This paper proposes a hybrid evaluation methodology for some non-governmental organizations enabling them to select the most competent expert who can properly and adequately develop and implement humanitarian projects. This methodology accommodates various stakeholders’ perspectives in satisfying the unique requirements of humanitarian projects that are capable of handling a range of uncertain issues from both stakeholders and project requirements. The criteria weights are calculated using a two-step multi-criteria decision-making method: (1) Fuzzy Analytical Hierarchy Process for the evaluation of the decision maker weights coupled with (2) Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank the alternatives which provide the ability to take into account both quantitative and qualitative evaluations. Sensitivity analysis have been developed and discussed by means of a real case of expert selection problem for a non-profit organisation. The results show that the approach allows a decrease in the uncertainty associated with decision-making, which proves that the approach provides robust solutions in terms of sensitivity analysis

A rare heterozygous TREM2 coding variant identified in familial clustering of dementia affects an intrinsically disordered protein region and function of TREM2

Rare coding variants in the triggering receptor expressed on myeloid cells-2 (TREM2) gene have been associated with Alzheimer disease (AD) and homozygous TREM2 loss-of-function variants have been reported in families with monogenic frontotemporal-like dementia with/without bone abnormalities. In a whole-exome sequencing study of a family with probable AD-type dementia without pathogenic variants in known autosomal dominant dementia disease genes and negative for the apolipoprotein E (APOE) ε4 allele, we identified an extremely rare TREM2 coding variant, that is, a glycine-to-tryptophan substitution at amino acid position 145 (NM_018965.3:c.433G>T/p.[Gly145Trp]). This alteration is found in only 1 of 251,150 control alleles in gnomAD. It was present in both severely affected as well as in another putatively affected and one 61 years old as yet unaffected family member suggesting incomplete penetrance and/or a variable age of onset. Gly145 maps to an intrinsically disordered region (IDR) of TREM2 between the immunoglobulin-like and transmembrane domain. Subsequent cellular studies showed that the variant led to IDR shortening and structural changes of the mutant protein resulting in an impairment of cellular responses upon receptor activation. Our results, suggest that a p.(Gly145Trp)-induced structural disturbance and functional impairment of TREM2 may contribute to the pathogenesis of an AD-like form of dementia

Reprint of "Decision support models for supplier development: Systematic literature review and research agenda"

The continuing trend towards sourcing components and semi-finished goods for less vertically integrated manufacturing systems globally leads to a dramatic increase in supply options for companies. To ensure that companies benefit from the potentials global sourcing offers, supplier-buyer relationships need to be managed efficiently. Due to the decreasing share of value-adding activities provided in-house, suppliers are more and more considered as an essential contributor to the buying company's competitive position. Consequently, to realize and sustain competitive advantages, companies try to establish institutionalized long-term relationships to their most important suppliers and to actively improve the productivity and performance of their supplier base. To support supplier development in practice, researchers have developed decision support models that provide assistance in selecting and implementing suitable supplier development activities. The aim of this paper is to provide a comprehensive and systematic overview of decision support models for supplier development and to develop a research agenda that helps to identify promising areas for future research in this area. First, typical applications for supplier development as well as potential development measures that can be adopted to improve the performance of suppliers are identified. Secondly, a systematic literature review with a focus on decision support models for supplier development is conducted. Based on the analysis of the literature, we define a research agenda that synthesizes key trends and promising research opportunities and thus highlight areas where more decision support models are needed to foster supplier development initiatives in practice

Brain Neuronal CB2 Cannabinoid Receptors in Drug Abuse and Depression: From Mice to Human Subjects

BACKGROUND: Addiction and major depression are mental health problems associated with stressful events in life with high relapse and reoccurrence even after treatment. Many laboratories were not able to detect the presence of cannabinoid CB2 receptors (CB2-Rs) in healthy brains, but there has been demonstration of CB2-R expression in rat microglial cells and other brain associated cells during inflammation. Therefore, neuronal expression of CB2-Rs had been ambiguous and controversial and its role in depression and substance abuse is unknown. METHODOLOGY/PRINCIPAL FINDINGS: In this study we tested the hypothesis that genetic variants of CB2 gene might be associated with depression in a human population and that alteration in CB2 gene expression may be involved in the effects of abused substances including opiates, cocaine and ethanol in rodents. Here we demonstrate that a high incidence of (Q63R) but not (H316Y) polymorphism in the CB2 gene was found in Japanese depressed subjects. CB2-Rs and their gene transcripts are expressed in the brains of naïve mice and are modulated following exposure to stressors and administration of abused drugs. Mice that developed alcohol preference had reduced CB2 gene expression and chronic treatment with JWH015 a putative CB2-R agonist, enhanced alcohol consumption in stressed but not in control mice. The direct intracerebroventricular microinjection of CB2 anti-sense oligonucleotide into the mouse brain reduced mouse aversions in the plus-maze test, indicating the functional presence of CB2-Rs in the brain that modifies behavior. We report for the using electron microscopy the sub cellular localization of CB2-Rs that are mainly on post-synaptic elements in rodent brain. CONCLUSIONS/SIGNIFICANCE: Our data demonstrate the functional expression of CB2-Rs in brain that may provide novel targets for the effects of cannabinoids in depression and substance abuse disorders beyond neuro-immunocannabinoid activity

CB2 Cannabinoid Receptors Contribute to Bacterial Invasion and Mortality in Polymicrobial Sepsis

BACKGROUND:Sepsis is a major healthcare problem and current estimates suggest that the incidence of sepsis is approximately 750,000 annually. Sepsis is caused by an inability of the immune system to eliminate invading pathogens. It was recently proposed that endogenous mediators produced during sepsis can contribute to the immune dysfunction that is observed in sepsis. Endocannabinoids that are produced excessively in sepsis are potential factors leading to immune dysfunction, because they suppress immune cell function by binding to G-protein-coupled CB(2) receptors on immune cells. Here we examined the role of CB(2) receptors in regulating the host's response to sepsis. METHODS AND FINDINGS:The role of CB(2) receptors was studied by subjecting CB(2) receptor wild-type and knockout mice to bacterial sepsis induced by cecal ligation and puncture. We report that CB(2) receptor inactivation by knockout decreases sepsis-induced mortality, and bacterial translocation into the bloodstream of septic animals. Furthermore, CB(2) receptor inactivation decreases kidney and muscle injury, suppresses splenic nuclear factor (NF)-kappaB activation, and diminishes the production of IL-10, IL-6 and MIP-2. Finally, CB(2) receptor deficiency prevents apoptosis in lymphoid organs and augments the number of CD11b(+) and CD19(+) cells during CLP. CONCLUSIONS:Taken together, our results establish for the first time that CB(2) receptors are important contributors to septic immune dysfunction and mortality, indicating that CB(2) receptors may be therapeutically targeted for the benefit of patients suffering from sepsis