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  • 1.
    Abedini, M.
    et al.
    Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.
    Ahmadzadeh, Farzaneh
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Noorossana, R.
    Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.
    Customer credit scoring using a hybrid data mining approach2016Ingår i: Kybernetes, ISSN 0368-492X, E-ISSN 1758-7883, Vol. 45, nr 10, s. 1576-1588Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Purpose: A crucial decision in financial services is how to classify credit or loan applicants into good and bad applicants. The purpose of this paper is to propose a four-stage hybrid data mining approach to support the decision-making process. Design/methodology/approach: The approach is inspired by the bagging ensemble learning method and proposes a new voting method, namely two-level majority voting in the last stage. First some training subsets are generated. Then some different base classifiers are tuned and afterward some ensemble methods are applied to strengthen tuned classifiers. Finally, two-level majority voting schemes help the approach to achieve more accuracy. Findings: A comparison of results shows the proposed model outperforms powerful single classifiers such as multilayer perceptron (MLP), support vector machine, logistic regression (LR). In addition, it is more accurate than ensemble learning methods such as bagging-LR or rotation forest (RF)-MLP. The model outperforms single classifiers in terms of type I and II errors; it is close to some ensemble approaches such as bagging-LR and RF-MLP but fails to outperform them in terms of type I and II errors. Moreover, majority voting in the final stage provides more reliable results. Practical implications: The study concludes the approach would be beneficial for banks, credit card companies and other credit provider organisations. Originality/value: A novel four stages hybrid approach inspired by bagging ensemble method proposed. Moreover the two-level majority voting in two different schemes in the last stage provides more accuracy. An integrated evaluation criterion for classification errors provides an enhanced insight for error comparisons.

  • 2.
    Ahmadzadeh, Farzaneh
    Islamic Azad University of Karaj Branch, Karaj, Tehran, Iran .
    Change point detection with multivariate control charts by artificial neural network2009Ingår i: International Journal of Advanced Manufacturing Technology IJAMT, ISSN 0268-3768, s. 1-12Artikel i tidskrift (Refereegranskat)
  • 3.
    Ahmadzadeh, Farzaneh
    Islamic Azad University, Iran.
    Diagnosing the Cause and Its Timing of Changes in Multivariate Process Mean Vector From Quality Control Charts Using Artificial Neural Network2011Ingår i: World Academy of Science, Engineering and Technology: An International Journal of Science, Engineering and Technology, ISSN 2010-376X, E-ISSN 2070-3740, Vol. 5, nr 6, s. 212-217Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Quality control charts are very effective in detecting out of control signals but when a control chart signals an out of control condition of the process mean, searching for a special cause in the vicinity of the signal time would not always lead to prompt identification of the source(s) of the out of control condition as the change point in the process parameter(s) is usually different from the signal time. It is very important to manufacturer to determine at what point and which parameters in the past caused the signal. Early warning of process change would expedite the search for the special causes and enhance quality at lower cost. In this paper the quality variables under investigation are assumed to follow a multivariate normal distribution with known means and variance-covariance matrix and the process means after one step change remain at the new level until the special cause is being identified and removed, also it is supposed that only one variable could be changed at the same time. This research applies artificial neural network (ANN) to identify the time the change occurred and the parameter which caused the change or shift. The performance of the approach was assessed through a computer simulation experiment. The results show that neural network performs effectively and equally well for the whole shift magnitude which has been considered.

  • 4.
    Ahmadzadeh, Farzaneh
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Multi criteria decision making with Evidential Reasoning under uncertainty2016Ingår i: IEEE International Conference on Industrial Engineering and Engineering Management, 2016, s. 1534-1538Konferensbidrag (Refereegranskat)
    Abstract [en]

    Many decision problems have more than one objective that need to be dealt with simultaneously. Moreover, because of the qualitative nature of the most of real world problem it is an inevitable activity and very important to interpret and present the uncertain information for making effective decision. The Evidential Reasoning (ER) approach which is one of the latest development within multi criteria decision making (MCDM) seems to be the best fit to synthesize both qualitative and quantitative data under uncertainty. To support this claim, two case studies were tested to illustrate the application of ER for prioritization and ranking of decision alternative to support decision process even with uncertain information. The importance of having a better structured decision process is essential for the success of any organization, so it can be applied widely in most of real world problem dealing with making effective decision.

  • 5.
    Ahmadzadeh, Farzaneh
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Ranking of Two Multi Criteria Decision Making Cases with Evidential Reasoning under Uncertainty2017Ingår i: Advances in Science, Technology and Engineering Systems Journal V2(3) ASTESJ-V2(3), ISSN 2415-6698, Vol. 2, nr 3, s. 1059-1063Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Many decision problems have more than one objective that need to be dealt with simultaneously. Moreover, because of the qualitative nature of the most of real world problem it is an inevitable activity and very important to interpret and present the uncertain information for making effective decision. The Evidential Reasoning (ER) approach which is one of the latest development within multi criteria decision making (MCDM) seems to be the best fit to synthesize both qualitative and quantitative data under uncertainty. To support this claim, two case studies were tested to illustrate the application of ER for prioritization and ranking of decision alternative to support decision process even with uncertain information. The overall goal of the first case study is to identify and prioritize factors that can be considered maintenance-related waste within the automotive manufacturing industry. The result after applying ER shows “inadequate resources” and “weather /indoor climate,” respectively, are the highest and lowest average scores for creating maintenance-related waste. This prioritization methodology can be used as a tool to create awareness for managers seeking to reduce or eliminate maintenance-related waste. The aim of the second case study is to look at the possibility of having a new approach for sustainable design. So through a literature review six design strategies were taken into consideration in order to develop a new approach based on all advantages (sustainable factors) of the six approaches. For ranking and finding out about the most important factors the evidential reasoning (ER) approach is used. Based on ER all the important factors, apart from the one collected from interviews are a part of eco-design. So it means among all strategies eco-design is the most dominant strategy in term of environment. However two of the important factors are not found in any strategy but in interviews. These factors can be used as the building blocks for a new approach. The importance of having a better structured decision process is essential for the success of any organization, so it can be applied widely in most of real world problem dealing with making effective decision.

  • 6.
    Ahmadzadeh, Farzaneh
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Bengtsson, Marcus
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Classification of Maintenance-Related Waste Based on Human Factors2015Ingår i: 22nd International Annual EurOMA Conference EurOMA15, Neuchâtel, Switzerland, 2015Konferensbidrag (Refereegranskat)
    Abstract [en]

    The goal of this research is to identify and classify factors creating maintenance-related waste. A workshop study has been performed in order to identify root-causes for maintenance-related waste. In total, 16 categories were found in the analysis and it is concluded that these are heavily reliant on human factors as a root- or major contributory cause. These, together with factors based on a literature review have been incorporated into a classification model. The model can be used in creating awareness in, as well as provide a basic framework for decision making of, which waste to target for elimination.

  • 7.
    Ahmadzadeh, Farzaneh
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Bengtsson, Marcus
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Using evidential reasoning approach for prioritization of maintenance-related waste caused by human factors-a case study2017Ingår i: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 90, nr 9-12, s. 2761-2775Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The reduction and elimination of maintenance-related waste is receiving increasing attention because of the negative effect of such waste on production costs. The overall goal of this research is to identify and prioritize factors that can be considered maintenance-related waste within the automotive manufacturing industry. Five manufacturing companies participated in a workshop to identify root causes of maintenance-related waste; 16 categories were found. The identified factors were heavily reliant on human factors as a root or major contributory cause at different levels affecting performance and productivity. For prioritization, the evidential reasoning (ER) approach which is one of the latest developments in multi-criteria decision-making is applied. A basic tree structure necessary for ER assessment is developed based on the workshop results as well as literature on human factors. Then, a survey on basic attributes at the lowest level of this tree is designed and performed at one of the companies participating in the workshop. The application of ER shows that, on an overall level, "management condition" is in first order and "maintainer condition" and "working condition" are in second and third order respectively as the worst cases for creating maintenance-related waste. On the most delimited level "inadequate resources" and "weather/indoor climate" have the highest and lowest average scores respectively in ER ranking or prioritization. This methodology with its resulting ranking can be used as a tool to create awareness for managers seeking to reduce or eliminate maintenance-related waste.

  • 8.
    Ahmadzadeh, Farzaneh
    et al.
    Luleå University of Technology, Sweden.
    Golshani Asl, Aliakbar
    Luleå University of Technology, Sweden.
    Risk Prioritization Based on Health, Safety and Environmental Factors by Using Fuzzy FMEA2013Ingår i: International Journal of Mining, Metallurgy & Mechanical Engineering, ISSN 2320-4052, Vol. 1, nr 4, s. 233-237Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Failure Mode and Effects Analysis is assessing technique which relies to the rule of preventing failure, which is used to identify potential hazards. This method is used with minimum risks to predict the problems and deficits in design stage or development of the processes and services in organizations. The methods main principal is based on multiplying three main parameters: severity, occurrence, detection. This method with all the advantages still has minor disadvantages that in this paper attempts has been made to eliminate these deficiencies by fuzzification. Results show that fuzzy FMEA will enables us to evaluate situations correctly and precisely.

  • 9.
    Ahmadzadeh, Farzaneh
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Jederström, Kathrina
    Mälardalens högskola.
    Plahn, Maria
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Olsson, Anna
    Mälardalens högskola.
    Foyer, Isabell
    Mälardalens högskola.
    AN INVESTIGATION OF THE MOST IMPORTANT FACTORS FOR SUSTAINABLE PRODUCT DEVELOPMENT USING EVIDENTIAL REASONING2017Ingår i: Numerical Algebra, Control and Optimization, ISSN 2155-3289, E-ISSN 2155-3297, Vol. 7, nr 4, s. 435-455Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Those working in product development need to consider sustain ability, being careful not to compromise the future generations ability to satisfy its needs. Several strategies guide companies towards sustainability. This paper studies six of these strategies: eco-design, green design, cradle-to-cradle, design for environment, zero waste, and life cycle approaches. Based on a literature review and semi-structured interviews, it identifies 22 factors of sustainability from the perspective of manufacturers. The purpose is to determine which are the most important and to use them as a foundation for a new design strategy. A survey based on the 22 factors was given to people working with product development; they graded each factor by importance. The resulting qualitative data were analyzed using evidential reasoning. The analysis found the factors minimize use of toxic substances, increase competitiveness, economic benefits, reduce material usage, material selection, reduce emissions, and increase product functionality are more important and should serve as the foundation for a new approach to sustainable product development.

  • 10.
    Ahmadzadeh, Farzaneh
    et al.
    Luleå University of Technology, Luleå, Sweden .
    Lundberg, J.
    Luleå University of Technology, Luleå, Sweden .
    Remaining useful life prediction of grinding mill liners using an artificial neural network2013Ingår i: Minerals Engineering, ISSN 0892-6875, E-ISSN 1872-9444, Vol. 53, s. 1-8Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Knowing the remaining useful life of grinding mill liners would greatly facilitate maintenance decisions. Now, a mill must be stopped periodically so that the maintenance engineer can enter, measure the liners' wear, and make the appropriate maintenance decision. As mill stoppage leads to heavy production losses, the main aim of this study is to develop a method which predicts the remaining useful life of the liners, without needing to stop the mill. Because of the proven ability of artificial neural networks (ANNs) to recognize complex relationships between input and output variables, as well as its adaptive and parallel information-processing structure, an ANN has been designed based on the various process parameters which influence wear of the liners. The process parameters were considered as inputs while remaining height and remaining life of the liners were outputs. The results show remarkably high degree of correlation between the input and output variables. The performance of the neural network model is very consistent for data used for training (seen) and testing (unseen).

  • 11.
    Ahmadzadeh, Farzaneh
    et al.
    Luleå University of Technology, Sweden.
    Lundberg, Jan
    Luleå University of Technology, Sweden.
    Application of multi regressive linear model and neural network for wear prediction of grinding mill liners2013Ingår i: International Journal of Advanced Computer Sciences and Applications, ISSN 2158-107X, E-ISSN 2156-5570, Vol. 4, nr 5, s. 52-58Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The liner of an ore grinding mill is a critical component in the grinding process, necessary for both high metal recovery and shell protection. From an economic point of view, it is important to keep mill liners in operation as long as possible, minimising the downtime for maintenance or repair. Therefore, predicting their wear is crucial. This paper tests different methods of predicting wear in the context of remaining height and remaining life of the liners. The key concern is to make decisions on replacement and maintenance without stopping the mill for extra inspection as this leads to financial savings. The paper applies linear multiple regression and artificial neural networks (ANN) techniques to determine the most suitable methodology for predicting wear. The advantages of the ANN model over the traditional approach of multiple regression analysis include its high accuracy.

  • 12.
    Ahmadzadeh, Farzaneh
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering. Luleå University of Technology, Luleå, Sweden.
    Lundberg, Jan
    Luleå University of Technology, Luleå, Sweden.
    Remaining useful life estimation: Review2014Ingår i: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, nr 4, s. 461-474Artikel, recension (Övrigt vetenskapligt)
    Abstract [en]

    This paper reviews the recent modelling developments in estimating the remaining useful life (RUL) of industrial systems. The RUL estimation models are categorized into experimental, data driven, physics based and hybrid approaches. The paper reviews some typical approaches and discusses their advantages and disadvantages. According to the literature, the selection of the best model depends on the level of accuracy and availability of data. In cases of quick estimations which are less accurate, the data driven method is preferred, while the physics based approach is applied when the accuracy of estimation is important.

  • 13.
    Ahmadzadeh, Farzaneh
    et al.
    Luleå University of Technology, Luleå, Sweden.
    Lundberg, Jan
    Luleå University of Technology, Luleå, Sweden.
    Strömberg, Thomas
    Luleå University of Technology, Luleå, Sweden.
    Multivariate process parameter change identification by neural network2013Ingår i: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 69, nr 9-12, s. 2261-2268Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Whenever there is an out-of-control signal in process parameter control charts, maintenance engineers try to diagnose the cause near the time of the signal which does not always lead to prompt identification of the source(s) of the out-of-control condition, and this in some cases yields to extremely high monetary loses for the manufacturer owner. This paper applies multivariate exponentially weighted moving average (MEWMA) control charts and neural networks to make the signal identification more effective. The simulation of this procedure shows that this new control chart can be very effective in detecting the actual change point for all process dimension and all shift magnitudes considered. This methodology can be used in manufacturing and process industries to predict change points and expedite the search for failure causing parameters, resulting in improved quality at reduced overall cost. This research shows development of MEWMA by usage of neural network for identifying the step change-point and the variable responsible for the change in the process mean vector.

  • 14.
    Al-Chalabi, H
    et al.
    Luleå University of Technology, Luleå, Sweden.
    Ahmadzadeh, Farzaneh
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Lundberg, J.
    Luleå University of Technology, Luleå, Sweden.
    Ghodrati, B.
    Luleå University of Technology, Luleå, Sweden.
    Economic lifetime prediction of a mining drilling machine using an artificial neural network2014Ingår i: International Journal of Mining, Reclamation and Environment, ISSN 1748-0930, E-ISSN 1748-0949, Vol. 28, nr 5, s. 311-322Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This study develops models for predicting the economic lifetime of drilling machines used in mining. It uses three cases, each represented by a MATLAB code, to develop an optimisation model. The resulting ORT is fed as input to an artificial neural network (ANN) and the results translated into a relatively simple equation. The study finds that increasing the purchase price and decreasing the operating and maintenance costs will increase a machine's ORT linearly. Decreased maintenance cost has the largest impact on ORT, followed by increased purchase price and decreased operating cost. The ANN method gives a series of basic weight and response functions which can be made available to any engineer without the use of complicated software. It also helps decision-makers determine the best time economically to replace an old machine with a new one; thus, it can be extended to more general applications in the mining industry.

  • 15.
    Bengtsson, Marcus
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Söderlund, Carina
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Salonen, Antti
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Chirumalla, Koteshwar
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Ahmadzadeh, Farzaneh
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Rastegari, Ali
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Handbok för att minska underhållsrelaterade slöserier2016Rapport (Övrigt vetenskapligt)
    Abstract [en]

    ENLIGT HEMSIDAN ”www.phrases.org.uk”(2016-02-25) myntade författaren Daniel Defoe frasen ’döden och skatter’ år 1726 och fler har sedan följt i hans fotspår. En av de kanske mest kända formuleringarna kom till i ett samtal mellan Benjamin Franklin och Jean-Baptiste Leroy (1789): ”I denna värld kan ingenting sägas vara säkert, utom döden och skatterna.” (fritt översatt från engelska). Vi har även funnit en person som använt det här uttrycket kopplat till underhåll, nämligen Kevin Marshall som diskuterar underhåll av hyreshus: ”...döden, skatter och underhåll.” (”www.flat-living.co.uk”, 2016-02-25). Underhåll i någon av alla dess former är någonting alla människor på jorden upplever nästan dagligen, medvetet eller omedvetet. Det finns egentligen bara ett sätt att tackla detta – med ett leende på läpparna. Man behöver dock inte vara slösaktig. På samma sätt som väldigt få vill betala mer i skatt än vad lagen kräver så vill sällan någon betala mer för underhåll än vad nöden kräver. Det är vad denna handbok handlar om. Den vänder sig till tillverkande företag som önskar minska sina underhållsrelaterade slöserier, och därför har behov av att se över sin verksamhet. Boken vänder sig i första hand till ledningsgrupper för underhåll, underhållschefer och underhållsutvecklare/ingenjörer. Dock, för att citera en av våra samarbetspartners: ”Det är ett slöseri om bara anställda inom underhållsavdelningen läser boken.” För att nå ett hållbart resultat är vi övertygade om att medvetenheten om slöserier och underhållsrelaterade slöserier behöver höjas bland samtliga anställda i en verksamhet. Detta är anledningen till att vi vill att du använder handboken. Vi uppmanar till att du läser exemplen och diskuterar frågorna med medarbetare inom hela underhållsavdelningen, och gärna tvärfunktionellt med produktion och övriga stödfunktioner. Vårt mål är att ge vägledning för hur tillverkande företag kan arbeta med underhållsrelaterade slöserier. Boken klargör vad sådana slöserier är, samt tips och idéer på hur man kan identifiera, klassificera och kvantifiera dem. Handboken presenterar även en arbetsprocess för att minska eller ta bort underhållsrelaterade slöserier så kostnadseffektivt som möjligt. Den innehåller också korta teoriavsnitt med exempel från praktiken och frågor som ledningsgrupper och anställda inom verksamheten kan diskutera. Genom att följa arbetsprocessen kan du och ditt företag få ökad medvetenhet och förståelse för underhållsrelaterade slöserier inom er egen verksamhet. Handboken fokuserar främst på de tidiga stegen i processen eftersom de är mest avgörande för ett lyckat resultat. Underhållsrelaterade slöserier är delvis unika för varje företag. Tyvärr finns inga genvägar eller standarder för att minska eller ta bort dem. Att endast läsa handboken kommer inte att ge något resultat. Den här boken bygger på att du och ditt företag aktivt finner er egen väg för att minska eller ta bort de underhållsrelaterade slöserier ni upptäcker i er verksamhet.

  • 16.
    Fataneh, Javadi
    et al.
    Islamic Azad University Karaj Branch, Iran.
    Ahmadzadeh, Farzaneh
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Mirzazadeh, Abolfazl
    University of Kharazmi, Tehran, Iran.
    Attribute Control Chart Development by Evidential Reasoning2014Ingår i: Proceedings of The 3rd international workshop and congress on eMaintenance, 2014, s. 37-40Konferensbidrag (Refereegranskat)
    Abstract [en]

    Attributes charts are commonly used in monitoring quality characteristics of the proportion type and these charts assume that the monitored characteristics are binomially distributed. Classical control charts need to certain and precise data. However, in practice, quality experts express their opinion in imprecise form, which in turn, add more uncertainty and ambiguity. It is essential to properly represent and interpret uncertain information to evaluate product items. In this paper, the evidential reasoning (ER) based approach has been developed for supporting this uncertainty. So the belief multinomial p-control chart is introduced for monitoring the production process in the uncertainty condition, using evidence theory and the belief structure. A numerical example showing production process evaluation is examined by using the ER approach. The results show the proposed approach, is effective not only for reducing production defective but also for increasing the certainty in interpreting of quality variables (data).

  • 17.
    Ghodrati, B.
    et al.
    Luleå University of Technology, Sweden.
    Ahmadzadeh, Farzaneh
    Luleå University of Technology, Sweden.
    Kumar, U.
    Luleå University of Technology, Sweden.
    Mean Residual Life Estimation Considering Operating Environment2012Ingår i: International Conference on Quality, Reliability, Infocom Technology and Industrial Technology Management ICQRITTM, 2012Konferensbidrag (Refereegranskat)
  • 18. Ghodrati, B.
    et al.
    Kumar, U.
    Ahmadzadeh, Farzaneh
    Remaining Useful Life Estimation of Mining Equipment: A Case Study2012Ingår i: Proceedings of MPES 2012, 2012Konferensbidrag (Refereegranskat)
  • 19.
    Jalal, Safari
    et al.
    Islamic Azad University, Karaj, Iran.
    Ahmadzadeh, Farzaneh
    LTU University, Luleå, Sweden.
    Multi objective allocation problem2012Ingår i: Proceedingsof The 2nd International Workshop and Congress on eMaintenance eMaintenance, 2012, s. 131-136Konferensbidrag (Refereegranskat)
  • 20.
    Mostafa Orand, Seyed
    et al.
    Islamic Azad University, Saveh Branch, Iran.
    Ahmadzadeh, Farzaneh
    Luleå University of Technology, Sweden.
    Mirzazadeh, Abolfazl
    Islamic Azad University, Karaj Branch, Iran.
    Application of particle swarm optimization approach in the inflationary inventory model under stochastic conditions2012Ingår i: Proceedings of The 2nd International Workshop and Congress on eMaintenance eMaintenance, 2012, s. 125-131Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents the inventory model considering inflation under non-deterministic situations, which can be used for arbitrary probability density function (pdf), for the inflation rate. We used two solution methods for determining the optimal ordering policy: (1) classical optimization method and (2) particle swarm optimization (PSO) method with comparing the results. The shortages are allowed and fully backlogged. A constant fraction of the on-hand inventory deteriorates per unit time, as soon as the item is received into inventory. The numerical examples are provided to explore the correctness of theoretical results, which are further clarified through a sensitivity analysis on the parameters of the model.

  • 21.
    Mostafa Orand, Seyed
    et al.
    Islamic Azad University, Science and Research Branch, Saveh, Iran .
    Mirzazadeh, Abolfazl
    Kharazmi University, Tehran, Iran.
    Ahmadzadeh, Farzaneh
    Islamic Azad University, Karaj Branch, Iran.
    Talebloo, Farid
    Sufi Razi, Zanjan, Iran.
    Optimisation of the Inflationary Inventory Control Model under Stochastic Conditions with Simpson Approximation: Particle Swarm Optimisation Approach2015Ingår i: Iranian Journal of Management Studies, ISSN 2008-7055, Vol. 8, nr 2, s. 203-220Artikel i tidskrift (Refereegranskat)
  • 22.
    Strömberg, T.
    et al.
    Luleå University of Technology.
    Ahmadzadeh, Farzaneh
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering.
    Excess action and broken characteristics for Hamilton-Jacobi equations2014Ingår i: Nonlinear Analysis, ISSN 0362-546X, E-ISSN 1873-5215, Vol. 110, s. 113-129Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We study propagation of singularities for Hamilton-Jacobi equations S t+H(t,x,λS)=0,(t,x)∈(0,∞)×ℝn, by means of the excess Lagrangian action and a related class of characteristics. In a sense, the excess action gauges how far a curve X(t) is from being action minimizing for a given viscosity solution S(t,x) of the Hamilton-Jacobi equation. Broken characteristics are defined as curves along which the excess action grows at the slowest pace possible. In particular, we demonstrate that broken characteristics carry the singularities of the viscosity solution.

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