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Khalili-Damghani K.,Islamic Azad University at Tehran | Abtahi A.-R.,University of Economic Sciences | Tavana M.,Philadelphia University
Reliability Engineering and System Safety | Year: 2013

In this paper, a new dynamic self-adaptive multi-objective particle swarm optimization (DSAMOPSO) method is proposed to solve binary-state multi-objective reliability redundancy allocation problems (MORAPs). A combination of penalty function and modification strategies is used to handle the constraints in the MORAPs. A dynamic self-adaptive penalty function strategy is utilized to handle the constraints. A heuristic cost-benefit ratio is also supplied to modify the structure of violated swarms. An adaptive survey is conducted using several test problems to illustrate the performance of the proposed DSAMOPSO method. An efficient version of the epsilon-constraint (AUGMECON) method, a modified non-dominated sorting genetic algorithm (NSGA-II) method, and a customized time-variant multi-objective particle swarm optimization (cTV-MOPSO) method are used to generate non-dominated solutions for the test problems. Several properties of the DSAMOPSO method, such as fast-ranking, evolutionary-based operators, elitism, crowding distance, dynamic parameter tuning, and tournament global best selection, improved the best known solutions of the benchmark cases of the MORAP. Moreover, different accuracy and diversity metrics illustrated the relative preference of the DSAMOPSO method over the competing approaches in the literature. © 2012 Elsevier Ltd. All rights reserved.


Tavana M.,Philadelphia University | Tavana M.,University of Paderborn | Abtahi A.-R.,University of Economic Sciences | Khalili-Damghani K.,Islamic Azad University at Tehran
Expert Systems with Applications | Year: 2014

Considering the trade-offs between conflicting objectives in project scheduling problems (PSPs) is a difficult task. We propose a new multi-objective multi-mode model for solving discrete time-cost-quality trade-off problems (DTCQTPs) with preemption and generalized precedence relations. The proposed model has three unique features: (1) preemption of activities (with some restrictions as a minimum time before the first interruption, a maximum number of interruptions for each activity, and a maximum time between interruption and restarting); (2) simultaneous optimization of conflicting objectives (i.e., time, cost, and quality); and (3) generalized precedence relations between activities. These assumptions are often consistent with real-life projects. A customized, dynamic, and self-adaptive version of a multi-objective evolutionary algorithm is proposed to solve the scheduling problem. The proposed multi-objective evolutionary algorithm is compared with an efficient multi-objective mathematical programming technique known as the efficient ε-constraint method. The comparison is based on a number of performance metrics commonly used in multi-objective optimization. The results show the relative dominance of the proposed multi-objective evolutionary algorithm over the ε-constraint method. © 2013 Elsevier Ltd. All rights reserved.


Tavana M.,Philadelphia University | Khalili-Damghani K.,Islamic Azad University at Tehran | Abtahi A.-R.,University of Economic Sciences
Expert Systems with Applications | Year: 2013

The prioritization of advanced-technology projects at the National Aeronautic and Space Administration (NASA) is a difficult task. This difficulty is due to the multiple and often conflicting objectives in addition to the inherent technical complexities and valuation uncertainties involved in the assessment process. As such, a systematic and transparent decision support framework is needed to guide the assessment process, shape the decision outcomes and enable confident choices to be made. Methods for solving Multi-Criteria Decision Making (MCDM) problems have been widely used to select a finite number of alternatives generally characterized by multiple conflicting criteria. However, applying these methods is becoming increasingly difficult for technology assessment in the space industry because there are many emerging risks for which information is not available and decisions are made under significant uncertainty. In this paper, we propose a hybrid fuzzy group decision support framework for technology assessment at NASA. The proposed objective framework is comprised of two modules. In the first module, the complicated structure of the assessment criteria and alternatives are represented and evaluated with the Analytic Network Process (ANP). In the second module, the alternative advanced-technology projects are ranked using a customized fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). We demonstrate the applicability of the proposed framework through a case study at the Kennedy Space Center. © 2012 Elsevier Ltd. All rights reserved.


Electrocardiographic methods still provide the bulk of cardiovascular diagnostics. Cardiac ischemia is associated with typical alterations in cardiac biosignals that have to be measured, analyzed by mathematical algorithms and allegorized for further clinical diagnostics. The fast growing fields of biomedical engineering and applied sciences are intensely focused on generating new approaches to cardiac biosignal analysis for diagnosis and risk stratification in myocardial ischemia. To present and review the state of the art in and new approaches to electrocardiologic methods for non-invasive detection and risk stratification in coronary artery disease (CAD) and myocardial ischemia; secondarily, to explore the future perspectives of these methods. In follow-up to the Expert Discussion at the 2008 Workshop on "Biosignal Analysis" of the German Society of Biomedical Engineering in Potsdam, Germany, we comprehensively searched the pertinent literature and databases and compiled the results into this review. Then, we categorized the state-of-the-art methods and selected new approaches based on their applications in detection and risk stratification of myocardial ischemia. Finally, we compared the pros and cons of the methods and explored their future potentials for cardiology. Resting ECG, particularly suited for detecting ST-elevation myocardial infarctions, and exercise ECG, for the diagnosis of stable CAD, are state-of-the-art methods. New exercise-free methods for detecting stable CAD include cardiogoniometry (CGM); methods for detecting acute coronary syndrome without ST elevation are Body Surface Potential Mapping, functional imaging and CGM. Heart rate variability and blood pressure variability analyses, microvolt T-wave alternans and signal-averaged ECG mainly serve in detecting and stratifying the risk for lethal arrythmias in patients with myocardial ischemia or previous myocardial infarctions. Telemedicine and ambient-assisted living support the electrocardiological monitoring of at-risk patients. There are many promising methods for the exercise-free, non-invasive detection of CAD and myocardial ischemia in the stable and acute phases. In the coming years, these new methods will help enhance state-of-the-art procedures in routine diagnostics. The future can expect that equally novel methods for risk stratification and telemedicine will transition into clinical routine.


Wagner U.,University of Economic Sciences
Quality Management in Health Care | Year: 2010

Objective: The more complex a medical device is, the more difficult it is to control the hazards associated with its use. A substantial percentage of harm or injuries to patients resulting from treatment can be attributed to errors. No one knows exactly how many victims have been claimed by medical errors. Studies from the United States and other countries show that 3% to 4% of all hospital patients suffer harm or injuries. This text is intended to provide a practice-oriented approach to the discussion of targeted improvement opportunities in connection with a superficial consideration of the sociotechnical system comprising the manufacturers, the medical devices, and the users in the health facilities. Method: Analysis of the risk reports received by the Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte) in connection with undesirable events involving the use of medical devices. Supplementary consideration of additional data from previous human factors research in the field of medicine. The evaluation period for the primary data focuses on the years 2005 to 2008. A differentiation is made between the error causal factors, man, and device. Results: A substantial percentage of the incidents that occurred can be attributed to human blunders. Within the scope of an evaluation of more than 16 000 risk reports in connection with medical devices, 5000 risk reports could not be directly attributed to the failure of a medical device. The lack of an error culture seems to be a considerable problem. Conclusion: The safe and reliable development and use of medical devices requires efficient and consistent risk management. Until now, human factors are not sufficiently considered when identifying sources of errors in sociotechnical systems. The useful data required for an extensive risk assessment are missing. An interface-overlapping method of solution is required which permits system-analytical and unbiased error handling and integrates all stakeholders. © 2010 Wolters Kluwer Health | Lippincott Williams & Wilkins.


Amri F.,University of Economic Sciences
Renewable and Sustainable Energy Reviews | Year: 2016

The current study inspects the nexus amongst energy consumption, FDI inflows and output in 75 countries meantime the period 1990–2010. We further examine this relationship with regard to developed as well as developing countries assembled from diverse geographic regions from the world. The present results display that there is proof of bidirectional linkage concerning FDI and output per capita, concerning renewable energy consumption and gross domestic product per capita and concerning non-renewable energy and gross domestic product per capita in the three groups of countries (developed, all, and developing). In addition, the judgments detect a bidirectional linkage concerning renewable energy consumption and FDI in developed countries. An increase of 1% rate in renewable energy participates to improving FDI by 0.185 % and at the same time an increase of FDI contributes to enhancing renewable energy by 0.292%. Nevertheless, in the case of all and developing countries, the results discover unidirectional link moving from foreign inflows to both sorts of energy. In conclusion, the policy recommendations of our empirical results are taken into consideration. © 2016 Elsevier Ltd


Kouakou A.K.,University of Economic Sciences
Energy Policy | Year: 2011

This paper examines the causal relationship between the electric power industry and the economic growth of Cote d'Ivoire. Using the data from 1971 to 2008, a test was conducted for the cointegration and Granger causality within an error correction model. Results from these tests reveal a bidirectional causality between per capita electricity consumption and per capita GDP. A unidirectional causality running from electricity consumption to industry value added appears in the short run. Economic growth is found to have great effects on electricity consumption and a reverse causality from electricity to economic growth may also appear. In the long run, there is a unidirectional causality between electricity and both GDP and industry value added. From these findings, we conclude that the country will be energy dependent in the long run and must therefore secure the production network from shortfalls to ensure a sustainable development path. Accordingly, government should adopt policies aimed at increasing the investment in the sector by stepping up electricity production from existing and new energy sources. © 2011 Elsevier Ltdl.


This paper reviews the use of organizational greenhouse gas (GHG) emissions data by investors. It then asks if comparisons between organizations may be affected by a specific aspect of GHG accounting methodology: the choice of organizational boundary. The effect of boundary choice is rarely quantified, but the paper draws together a limited number of cases where this has been done. One case is found in which a different boundary choice changes the scope 1 emission figure by 73%. The paper presents exploratory interview evidence on organizations’ reasons for boundary selection and then reviews the approach taken in the recently introduced UK mandatory carbon reporting regulations. It concludes that further research is justified on the effect of boundary choice on corporate GHG emission figures and that the approach of the Climate Change Reporting Framework may offer a path to comparable data while allowing reporting organizations some flexibility. © 2016 Informa UK Limited, trading as Taylor & Francis Group


Lafratta G.,University of Economic Sciences
Advances in Intelligent Systems and Computing | Year: 2016

Multiple classification rules are simultaneously identified by applying the Cross-Entropy method to the maximization of accuracy measures in a supervised learning context. Optimal ensembles of rules are searched through stochastic traversals of the rule space. Each rule contributes to classify a given instance when the observed attribute values belong to specific subsets of the corresponding attribute domains. Classifications of the various rules are combined applying majority voting schemes. The performance of the proposed algorithm has been tested on some data sets from the UCI repository. © Springer International Publishing Switzerland 2016.


Falkowski J.,University of Economic Sciences
Agricultural Economics | Year: 2012

Numerous studies have shown that processing and retail industries have actively assisted farmers in joining the modern food marketing systems. Data from the Polish dairy sector show that assistance is provided not only for the traditional-channel farmers wishing to modernize, but also for farmers already included in the modern marketing channel. Two explanations can be provided to account for this phenomenon. One, even modern-channel farmers may lack sufficient funds to maintain required quality/quantity on their own. Two, it may be the case that even after undertaking necessary adjustments, modern-channel farmers are more likely to quit their relationship with a processor and turn elsewhere, in which case assistance is provided to prevent them from defecting. Using farm-level data, we investigate the impact of supply chain modernization on farmers' access to credit and their loyalty toward processors. Our results do not provide compelling evidence to support either hypothesis, suggesting at most a partial explanation for the existence of vertical linkages between processors and modern-channel farmers in Poland. © 2011 International Association of Agricultural Economists.

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