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Volume 16, Issue 2, 2009
Transaction on Industrial Engineering


Optimizing a Joint Economic Lot Sizing Problem with Price-Sensitive Demand
 
        M.R. Akbari Jokar (PhD.)
  • M. Sheikh Sajadieh [MSc.]

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This paper considers the problem of a vendor-buyer integrated production-inventory model. The vendor manufactures the item at a nite rate and delivers the nal goods at a lot-for-lot shipment policy to the buyer. We relax the assumption of uniform demand in the hitherto existing joint economic lot sizing models and analyze the problem where the end customer demand is price-sensitive. The relation between demand and price is considered to be linear. The model proposed, based on the integrated expected total relevant pro ts of both buyer and vendor, nds out the optimal values of order quantity and mark-up percentage, using an analytical approach. Some numerical examples are also used to analyze the e ect of the price-sensitivity of demand on the improvements in joint total pro t over individually derived policies.

Keywords:
Joint economic lot sizing

    Mark-up pricing policy
      Price-sensitive demand.


An Ecient Procedure for Computing an Optimal (R,Q) Policy in Continuous Review Systems with Poisson Demands and Constant Lead Time
 
        A. Eshraghnia Jahromi (PhD.)
  • N. Yazdan Shenas [MSc.]
  • M. Modarres Yazdi [Professor]

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In this paper, a continuous review inventory system is considered in which an order in a batch of size Q is placed immediately after the inventory position reaches R. Transportation time is constant and demands are assumed to be generated by a stationary Poisson process with one unit demand at a time. Demands not covered immediately from the inventory are backordered. In a recent paper, the exact evaluation of batch-ordering policies for two-level inventory systems was derived. This evaluation is based on a recursive procedure for determining the exact policy costs in case of one-for-one replenishment policies. In this paper, we show how this result can be applied to nd the optimal solution of a (R;Q) policy. To obtain the optimal policy for this system, considering a one-for-one policy, we will rst solve the base stock model by setting the inventory position at the supplier to a certain value. By considering ordering cost, we next derive the cost function of the de ned (R;Q) model and nd the optimal solution for the exact value of the expected system costs using a search method. In demonstrating the applicability of the proposed method, we resort to solving an example.

Keywords:
Inventory

    Continuous review
      (R;Q) model
        Base stock model
          Poisson demand
            Optimal solution
              Backordered demand
                Constant lead time.


Fuzzy Image Processing for Diagnosing In ammation in Pulmonary Biopsies
 
        M.H. Fazel Zarandi (PhD.)
  • M. Moeen [PhD.]
  • Sh. Norouzzadeh [PhD.]
  • Sh. Teimourian [PhD.]

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This paper proposes a new approach to diagnose the degree of in ammation in digital images of pulmonary biopsies, provided by a digital camera through a microscope. Diagnosing is done by detecting thick epithelium cell layers around the vessels and bronchus in tissue images. For analyzing the complex images of tissue, a fuzzy image processing procedure consisting of ve main stages is presented. The rst stage is decreasing the complexity of the images by using image pre-processing methods for enhancement and smoothing the image with a Gaussian low pass lter in order to highlight important details and ignore the unnecessary parts of the image. The second stage is segmentation by using a fuzzy c-means clustering algorithm and fuzzy canny edge detection. This step works as a data reduction method as well as object recognition. Feature extraction, the third stage, will be done by using a fuzzy Hough transform. After extracting features such as bronchioles and vessels from the image, the fourth stage will be analysis and reasoning by a fuzzy inference system, which is a hybrid of the Mamdani and Logical modeling system with a Yager parametric operator. The last stage is tuning system parameters and the learning process with a feed forward neural network. The output of the proposed algorithm is the degree of in ammation inferred by the fuzzy inference system. The proposed approach is user friendly with low computational time and the results are more precise, reliable and acceptable to experts and physicians.

Keywords:
Image processing

    Fuzzy modeling
      Fuzzy cluster analysis
        In ammation
          Pulmonary
            Canny edge detection
              Hough transform
                RGB image.


Two-Pillar Risk Management (TPRM): A Generic Project Risk Management Process
 
        M. A. Hatefi (PhD.)
  • S. M. Seyedhoseini [PhD.]

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A conventional Risk Management Process (RMP) contains two main phases: (a) risk assessment that includes risk identi cation and risk analysis, and (b) risk response that decides what, if anything, should be done about the analyzed risks. Based on a traditional tendency, most studies in stateof- the art RMP have ample emphasis on risk assessment, but we can nd limited studies on the subject of risk response. This paper aims to oppose the mentioned traditional view. The paper introduces a generic RMP, namely Two-Pillar Risk Management (TPRM) that considers an equivalent importance for both risk assessment and risk response. The paper compares the TPRM with the last version of the RMP provided in the standard of PMBoK. Application of the proposed model in projects in the construction industry shows a tremendous total risk level improvement. We believe that applying the TPRM helps project managers in a most e ective and ecient manner in dealing with their risk management programs.

Keywords:
Risk Management Process (RMP)

    Project risk management
      Risk response.


A Solution for Transportation Planning in Supply Chain
 
        A. Modares (PhD.)
  • M. Sepehri [PhD.]

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An advanced optimization system for Vehicle Routing and Scheduling Problems (VRSP), which is one of the Supply Chain Planning modules, is introduced. An object oriented system, Computer Aided Routing and Scheduling (CARS) can handle complicated distribution models using advanced heuristic optimization algorithms. To classify various types of routing and scheduling problems in a structured manner, a classi cation scheme is introduced based on the main objects of VRSP. Also, the modeling and solution approach in the CARS optimization engine has been elaborated. Main static and dynamic objects of the system as well as their relationships and interactions have been explained. The user interface in addition to the planning and operational features of the system is described in detail.

Keywords:
Vehicle routing

    Logistics
      Supply chain planning
        Advanced optimization system.


Lot Sizing and Lead Time Quotations in Assembly Systems
 
        G. Mokhtari (PhD.)
  • F. Kianfar [Professor]

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In this paper, a simultaneous lead time quotation and lot sizing problem in an assembly system is investigated. We address a production system with a product that has deterministic demand over a T-period planning horizon and is produced in lots because of the economy of scale. If a lot is completed before the demand period, inventory carrying cost is incurred. On shortages, a lead time is quoted to customers and a lead time quotation cost is incurred. Finally, if the order is delivered later than its due date period, a tardiness cost is charged. The components supply lead time is stochastic, which follows a discrete distribution. The problem is to decide on the lot size of products and components, supply and production starting periods and the due date of lots (to be quoted to customers) so that relevant costs are minimized. The objective function is the sum of the production, inventory carrying, lead time quotation and tardiness costs. We develop a genetic algorithm to solve the proposed model. An experimental framework is set up to test the eciency of the proposed method, which turns out to rate high, both in terms of cost e ectiveness and execution speed.

Keywords:
Lot-sizing

    Lead time quotation
      Genetic algorithms
        Production planning.


Concurrent Project Scheduling and Material Planning: A Genetic Algorithm Approach
 
        S. Shadrokh (PhD.)
  • M. Sheikh Sajadieh [MSc.]
  • F. Hassanzadeh [PhD.]

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Scheduling projects incorporated with materials ordering results in a more realistic problem. This paper deals with the combined problem of project scheduling and material ordering. The purpose of this paper is to minimize the total cost of this problem by determining the optimal values of activity duration, activity nish time and the material ordering schedule subject to constraints. We employ a genetic algorithm approach to solve it. Elements of the algorithm, such as chromosome structure, un tness function, crossover, mutation and local search operations are explained. The results of the experimentation are quite satisfactory.

Keywords:
Project scheduling

    Genetic algorithm
      Material ordering