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Volume 16, Issue 1, 2009
Transaction on Industrial Engineering


Multi Attribute Decision Making on Inter-Basin Water Transfer Projects
 
        F. Szidarovszky (PhD.)
  • M. Zarghami [PhD.]
  • R. Ardakanian [PhD.]

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One of the best ways to control water shortages in the Central Region of Iran is inter-basin water transfer (IBWT). Efficient decision making on this subject is however a real challenge for the water authorities in Iran. These decisions should include multiple attributes, model uncertainty, and also the optimistic/pessimistic view of the decision makers. The Ordered Weighted Averaging (OWA) operator can be used as an efficient multi attribute decision making (MADM) method. This paper will introduce a new method to obtain the order weights of this operator. The new method is based on the combination of fuzzy quantifiers and neat OWA operators. Fuzzy quantifiers are applied for soft computing in modeling the optimism degree of the decision maker. In using neat operators, the ordering of the inputs is not needed resulting in better computation efficiency. The theoretical results will be illustrated in a case study by solving an MADM problem with four IBWT projects for the Zayanderud basin. The results demonstrate that more sensitive decisions can be obtained by using the new method.


A Hybrid Scatter Search for the Resource-Constrained Project Scheduling Problem
 
        M. Ranjbar (PhD.)
  • F. Kianfar [Professor]

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Abstract In this paper we develop a new hybrid metaheuristic algorithm based on the scatter search approach to solve the well-known resource-constrained project scheduling problem. This algorithm combines two solutions from scatter search to build a set of precedence feasible activity lists and select some of them as children for the new population. We use the idea presented in the forward/backward improvement technique to define two types of schedule, direct and reverse, and the members of the sequential populations change alternately between these two types of schedule. Extensive computational tests were performed on standard benchmark datasets and the results are compared with the best available results. Comparative computational tests indicate that our procedure is a very effective metaheuristic algorithm.

Keywords:
Project scheduling

    Metaheuristic
      Scatter search


Replacement–repair policy based on simulation model for multi-state deteriorating products under warranty
 
        A. Eshraghnia Jahromi (PhD.)
  • H. Vahdani [MSc.]

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Abstract In this paper a replacement-repair model is developed to study a warranty servicing policy for a class of multi-state deteriorating and repairable products based on a computer simulation analysis. In each working state there is a determined probability for transition to each of the subsequent states, given that it has made a transition out of that state. There are two parameters that determine the manufacturer’s decision to repair or replace a failed item assuming that buyer’s claim is valid, the deterioration degree of the item and the length of the residual warranty period. Beside these two parameters, other inputs to the model are

    the number of working and failure states, the different rates of transition from each working state given that the life distribution is exponential, the length of entire warranty period, the probabilities of transition between states, the cost of repair and replacement in each failure state. The output of the model is the mean and standard deviation of the total simulated costs generated for a given set of inputs and such that the best values of the two mentioned parameters can be obtained based on the statistical test. The model is validated by comparing its output with the optimal expected costs generated by a mathematical approach for a few special situations where this comparison is possible.

    Keywords:
    warranty
      multi-state
        simulation
          deteriorating product.


Investigation of Impact of Supply Chain Integration on Product Innovation and Quality
 
        S. R. Hosseini Baharanchi (PhD.)

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Abstract This paper addresses integration issues in supply chain, and tries to investigate how different aspects of integration are linked with some product features. Integration in this study is interpreted as "internal", "upstream" (supply), and "downstream" (demand). Two product features which are considered in this study are "product innovation" and "product quality". To examine the relationships between supply chain integrations – as mentioned above, and product features, this research follows the survey method in automotive industry. The results imply that comparing to internal and supply chain downstream integrations supply chain upstream integration has a higher impact on product quality. It is also found that the influence of supply chain downstream integration on product innovation is greater than other variables. In brief, this study mainly tackles the importance of specific level of supply chain integrations and its effects on two product features.

Keywords:
Supply chain upstream integration, supply chain downstream integration, internal integration, product features


Designing an Optimum Acceptance Sampling Plan Using Bayesian Inferences and Stochastic Dynamic Programming Approach
 
        S.T. Akhavan Niaki (Professor)
  • M. S. Fallah Nezhad [PhD.]

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Abstract In this paper, we use both the stochastic dynamic programming and Bayesian inferences concepts to design an optimum-acceptance-sampling-plan policy in quality control environments. To determine the optimum policy we employ a combination of costs and risk functions in the objective function. Unlike previous studies, accepting or rejecting a batch are directly included in the action space of the proposed dynamic programming model. Using the posterior probability of the batch to be in state p (the probability of non-conforming products), first we formulate the problem into a stochastic dynamic programming model. Then, we derive some properties for the optimal value of the objective function, which enable us to search for the optimal policy that minimizes the ratio of the total discounted system cost to the discounted system correct choice probability.

Keywords:
Quality inspection

    Acceptance sampling plan
      Bayesian inference
        Stochastic Dynamic programming


Robot Movements in a cyclic multiple-part type Three-machine Flexible Robotic Cell problem
 
        I.N. Kamal Abadi (PhD.)
  • S. Gholami [PhD.]

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Abstract This paper recognizes thirty-six potentially optimal robot movement policies to schedule, movements of a robot in a three-machine flexible cell. The robotic cell produces multi-type parts in which the robot is used as material handling system. In this manufacturing cell the machines have operational flexibility and can be set up for different operations, and all parts have three operations. Finding the robot movement policy and sequence of parts to minimize cycle time (i.e.

    maximize the throughput) is the aim of this work. It was proved that cycle time calculation in twelve policies out of thirty-six policies, are unary NP-complete, and a polynomial time algorithms is introduced that can solve the twenty-four left policies. This paper develops cycle times of all these thirty six robot movements policies where considering waiting times in a flexible three machine robotic cell with multi-type parts, and introduces parts sequence in a special condition that one of the policies minimize the cycle time (i.e. maximize throughput). This kind of flexibility is differing from the other researches in robotic cells that a machine can process different operations, moreover we consider cells with multiple part types which is more realistic than other developed models. Finally a new mathematical model based on Petri nets provided, for one of robot movement policies. Further this mathematical model is developed for the multi-type part problem.

    Keywords:
    Production Scheduling, Cyclic blocking Open shop, Flexible Robotic Cell


A branch and bound algorithm for the weighted earliness-tardiness project scheduling problem with generalized precedence relations
 
        B. Afshar Nadjafi (PhD.)
  • S. Shadrokh [PhD.]

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Abstract We present an exact solution procedure for the weighted earliness-tardiness project scheduling problem (WETPSP) with generalized precedence relations (WETPSP-GPR), taking into account time value of money (WETPSPDC-GPR) and a fixed deadline for the project. The WETPSP-GPR extends the WETPSP to arbitrary minimal and maximal time-lags between the starting and completion times of activities. We present a new depth-first branch and bound (B&B) algorithm for extended form of the problem, which time value of money is taken into account by discounting the cash flows and minimum as well as maximum time-lags between different activities may be given. The algorithm is extended with two bounding rules in order to reduce the size of the branch and bound tree. Finally, some test problems are solved and computational results are reported.

Keywords:
Project scheduling

    Branch and bound
      Net present value
        generalized precedence relations


Service Quality Prioritization in various environments (A Cross-cultural comparison)
 
        R. Mostaghel (PhD.)
  • A. Albadvi [PhD.]

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Abstract The findings of this research are mostly useful to those who intend to penetrate international “Business to Consumer” markets. One of the key challenges of online businesses is how they manage service quality, which holds a significant importance to customer satisfaction. This paper is purposed to unveil customers’ perceptions on service quality priority and different cultures’ expectations in online shopping. The questionnaire utilized, was based on the SERVQUAL instrument that identifies five quality dimensions. This study indicates that in the developing countries customers need more security and clarity in transactions. The managerial and theoretical implications are provided. Key Words: Electronic commerce, online retailing, service quality.


Special Classes of Fuzzy Integer Programming Models with All-different Constraints
 
        K. Eshghi (Professor)
  • J. Nematian [PhD.]

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Abstract: In this paper, a fuzzy approach is applied to special classes of integer programming problems with all different constraints. In the first model, a fuzzy integer programming model is developed to represent the all-different constraints in mathematical programming. In order to solve the proposed model, a new branching scheme for the B&B algorithm is also presented. In the second model, a special class of large-scale multi-objective fuzzy integer programming problems with all-different constraints is introduced. A solution method for the proposed model is also developed by using the decomposition technique, weighting method and B&B algorithm. An illustrative numerical example is also given to clarify the theory and the method discussed in this paper.

Keywords:
Fuzzy integer programming, all-different constraints, Branch & Bound algorithm