Articles in Press
   2010
 
Transaction on Civil Engineering

Volume 17, Issue 1
Transaction on Civil Engineering
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Transaction on Civil Engineering
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Transaction on Civil Engineering
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Transaction on Civil Engineering
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Transaction on Civil Engineering
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Transaction on Civil Engineering
 
Transaction on Mechanical Engineering

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Transaction on Mechanical Engineering
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Transaction on Mechanical Engineering
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Transaction on Mechanical Engineering
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Transaction on Mechanical Engineering
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Transaction on Mechanical Engineering
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Transaction on Mechanical Engineering
 
Transactions on Chemistry and Chemical Engineering

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Transactions on Chemistry and Chemical Engineering
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Transactions on Chemistry and Chemical Engineering
 
Transaction on Computer Science & Engineering and Electrical Engineering

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Transaction on Computer Science & Engineering and Electrical Engineering
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Transaction on Computer Science & Engineering and Electrical Engineering
Transaction on Industrial Engineering

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Transaction on Industrial Engineering
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Transaction on Industrial Engineering
Transaction on Nanotechnology

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Transaction on Nanotechnology
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Transaction on Nanotechnology
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Volume 17, Issue 2, 2010
Transaction on Industrial Engineering


A New Rolling-Horizon Technique for Lotsizing in a Capacitated Pure Flow Shop with Sequence-Dependent Setups
 
        S. M. T. Fatemi Ghomi (Professor)
  • M. Mohammadi [PhD.]

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A new rolling-horizon approach is presented in this paper to solve the problem of lotsizing in a capacitated pure ow shop with sequence dependent setups. Two solution algorithms are provided, based on a simplified version of the problem, combining the rolling-horizon approach with a heuristic. To evaluate the effectiveness of the proposed algorithms, a comparison is made between the results obtained by the proposed algorithms and those obtained by existing algorithms. The comparison indicates the superiority of the proposed algorithm for large scale problems.

Keywords:
Lotsizing

    Scheduling
      Pure ow shop
        Sequence-dependent
          Rolling-horizon
            Multi-level.


An Exponential Cluster Validity Index for Fuzzy Clustering with Crisp and Fuzzy Data
 
        M. H. Fazel Zarandi (Professor)
  • M. R. Faraji [MSc.]
  • M. Karbasian [PhD.]

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This paper presents a new cluster validity index for finding a suitable number of fuzzy clusters with crisp and fuzzy data. The new index, called the ECAS-index, contains exponential compactness and separation measures. These measures indicate homogeneity within clusters and heterogeneity between clusters, respectively. Moreover, a fuzzy c-mean algorithm is used for fuzzy clustering with crisp data, and a fuzzy k-numbers clustering is used for clustering with fuzzy data. In comparison to other indices, it is evident that the proposed index is more e ective and robust under different conditions of data sets, such as noisy environments and large data sets.

Keywords:
Fuzzy clustering

    Cluster validity index
      Fuzzy c-mean algorithm
        Fuzzy k-numbers clustering
          Fuzzy numbers
            Compactness
              Separation.


A Cumulative Binomial Chart for Uni-variate Process Control
 
        M.S. Owlia (PhD.)
  • M. S. Fallah Nezhad [PhD.]

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In this paper, a control method based on binomial distribution is proposed in which, by analyzing the cumulated data for a uni-variate quality characteristic, the possible mean shift is detected. In this method, the domain of observations is rst divided into some speci ed intervals and then the number of observations in each interval is counted. Control statistics are next de ned using the counted values based on the approximation methods. Necessary adaptations are made to form an appropriate statistic for the process monitoring. Using a simulation technique, the performance of the proposed method is compared with the ones of the optimal EWMA, GEWMA, CUSUM and GLR control charts. The results show that with an equal in-control average run length, the cumulative Binomial control method performs better than control charts in detecting a mean shift of any size less than 3. The analysis is also carried out for autocorrelated data, showing that the proposed method performs better than other methods for small to moderate values of autocorrelation coecients.

Keywords:
Statistical process control

    Binomial distribution
      Cumulative data
        Simulation.


Optimal Ordering Policy Under Acceptance Sampling Plan and Trade Credit Financing
 
        T-C. Tsao (PhD.)

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Acceptance of sampling plans and trade credit has become increasingly common in today's business. These two issues should be considered simultaneously when determining an ordering decision. This paper uses EOQ to model the decision under the acceptance sampling plan and trade credit

    meaning, how often it would be necessary to order to minimize the total related cost. We develop theorems based on optimum lemmas to solve the problem. Computational analyses are given to illustrate the solution procedures and we discuss the in uence of credit period, acceptance sampling plan, holding cost and ordering cost on the total cost, and the ordering decision. We conclude with a computational analysis that leads to a variety of managerial insights.

    Keywords:
    Ordering
      Inventory
        Acceptance sampling plan
          Trade credit
            Optimization.


A Fuzzy Rule-Based Expert System for Diagnosing Asthma
 
        M. H. Fazel Zarandi (Professor)
  • M. Zolnoori [MSc.]
  • M. Moin [Professor]
  • H. Heidarnejad [Professor]

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Asthma is a chronic lung disorder of which the number of su erers estimated to be between 1.4-27.1% of the population in di erent areas of the world. Results of various studies show that asthma is usually under-diagnosed, especially in developing countries, because of limited access to medical specialist and laboratory data. The purpose of this paper is to design a fuzzy rule-based expert system to alleviate this hazard by diagnosing asthma at initial stages. A knowledge representation of this system is provided from a high level, based on patient perception, and organized into two di erent structures called Type A and Type B. Type A is composed of six modules, including symptoms, allergic rhinitis, genetic factors, symptom hyper-responsiveness, medical factors and environmental factors. Type B is composed of 8 modules including symptoms, allergic rhinitis, genetic factors, response to short-term drug use, bronchodilator tests, challenge tests, PEF tests and exhaled nitric oxide. The nal result of every system is de-fuzzi ed in order to provide the assessment of the possibility of asthma for the patient. Veri cation and validations criteria are considered throughout a life-cycle

    the system was developed by the participation of general physicians, experienced asthma physicians and asthmatic patients.

    Keywords:
    Fuzzy sets
      Medical expert system
        Asthma
          Diagnosis.


Determination of the Number of Kanbans and Batch Sizes in a JIT Supply Chain System
 
        S.K. Chaharsooghi (PhD.)
  • A. Sajedinejad [MSc.]

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Under stochastic demand in the multi-stage SCM in a JIT environment, the probability of generating a function of the stationary distributions of the backlogged demand was extended. The batch size of WIPs has a great impact on the packing, unpacking or transferring costs of a chain

    it has been attempted to integrate the delivery batch size of each plant in a multi-stage serial chain with the production-ordering and supplier kanbans of the chain. An algorithm was developed to evaluate the optimal numbers of kanbans and batch sizes of each plant by minimizing the total cost of a chain. A numerical example is also provided to indicate the signi cance of adding the proposed assumptions, as well as demonstrating the approach adopted towards solving the problem.

    Keywords:
    Supply chain
      JIT
        Stochastic demand
          Batch size
            Kanban.


Fuzzy Development of Multivariate Variable Control Charts Using the Fuzzy Likelihood Ratio Test
 
        S. M. T. Fatemi Ghomi (Professor)
  • H. Moheb Alizadeh [MSc.]
  • A. R. Arshadi Khamseh [PhD.]

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This paper is an e ort to evolve multivariate variable control charts in a fuzzy environment where each observation in each sample is assumed to be a canonical fuzzy number. To do this, a likelihood ratio test should be exploited in a fuzzy environment, because multivariate variable control charts are constructed using this test. In this way, membership functions of likelihood ratio statistics applied to control the process mean and dispersion are obtained solving four non-linear programming problems. Using these membership functions, membership degrees of in and out of control states of both process mean and dispersion are computed. Hence contrary to the classic multivariate variable control charts categorizing the process into just two states, i.e. in and out of control, the process can be considered in several intermediate states, based on the computed membership degrees, bringing about more exibility in process analysis.

Keywords:
Multivariate control charts

    Likelihood ratio test
      Non-linear programming
        Fuzzy numbers; Fuzzy random variables.