فهرست مطالب

International Journal of Industrial Engineering and Productional Research
Volume:22 Issue: 3, Sep 2011

  • تاریخ انتشار: 1390/07/24
  • تعداد عناوین: 8
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  • Mohammad Saber Fallah Nezhad, Hasan Hosseini Nasab Page 143
    In this research, a new control policy for the acceptance sampling problem is introduced. Decision is made based on the number of defectives items in an inspected batch. The objective of the model is to find a constant control level that minimizes the total costs, including the cost of rejecting the batch, the cost of inspection and the cost of defective items. The optimization is performed by approximating the negative binomial distribution with Poisson distribution and using the properties of binomial distribution. A solution method along with numerical demonstration on the application of the proposed methodology is presented. Furthermore, the results of sensitivity analysis show that the proposed method needs a large sample size.
  • E. Teimoury, I.G. Khondabi, M. Fathi Page 151
    The distribution center location problem is a crucial question for logistics decision makers. The optimization of these decisions needs careful attention to the fixed facility costs, inventory costs, transportation costs and customer responsiveness. In this paper we study the location selection of a distribution center which satisfies demands with a M/M/1 finite queueing system plus balking and reneging. The distribution center uses one for one inventory policy, where each arrival demand orders a unit of product to the distribution center and the distribution center refers this demand to its supplier. The matrix geometric method is applied to model the queueing system in order to obtain the steady-state probabilities and evaluate some performance measures. A cost model is developed to determine the best location for the distribution center and its optimal storage capacity and a numerical example is presented to determine the computability of the results derived in this study.
  • M. Miranbeigi, A.A. Jalali, A. Miranbeigi Page 159
    Supply chain networks are interconnection and dynamics of a demand network. Example subsystems, referred to as stages, include raw materials, distributors of the raw materials, manufacturers, distributors of the manufactured products, retailers, and customers. The main objectives of the control strategy for the supply chain network can be summarized as follows: (i) maximize customer satisfaction, and (ii) minimize supply chain operating costs. In this paper, we applied receding horizon control (RHC) method to a set of large scale supply chains of realistic size under demand disturbances adaptively. Also in order to increase the robustness of the system, we added a move suppression term to cost function.
  • M. Mohammadi, R. Tavakkoli-Moghaddam, A. Ghodratnama, H. Rostami Page 171
    Hub location problems (HLP) are synthetic optimization problems that appears in telecommunication and transportation networks where nodes send and receive commodities (i.e., data transmissions, passengers transportation, express packages, postal deliveries, etc.) through special facilities or transshipment points called hubs. In this paper, we consider a central mine and a number of hubs (e.g., factories) connected to a number of nodes (e.g., shops or customers) in a network. First, the hub network is designed, then, a raw materials transportation from a central mine to the hubs (i.e., factories) is scheduled. In this case, we consider only one transportation system regarded as single machine scheduling. Furthermore, we use this hub network to solve the scheduling model. In this paper, we consider the capacitated single allocation hub covering location problem (CSAHCLP) and then present the mixed-integer programming (MIP) model. Due to the computational complexity of the resulted models, we also propose two improved meta-heuristic algorithms, namely a genetic algorithm and a shuffled frog leaping algorithm in order to find a near-optimal solution of the given problem. The performance of the solutions found by the foregoing proposed algorithms is compared with exact solutions of the mathematical programming model.
  • Mohammad Ranjbar Page 181
    We consider a project scheduling problem with permitted tardiness and discrete time/resource trade-offs under maximum net present value objective. In this problem, a project consists of a set of sequential phases such that each phase contains one or more sub-projects including activities interrelated by finish-start-type precedence relations with a time lag of zero, which require one or more renewable resources. There is also a set of unconstrained renewable resources. For each activity, instead of a fixed duration and known resource requirements, a total work content respect to each renewable resource is given which essentially indicates how much work has to be performed on it. This work content can be performed in different modes, i.e. with different durations and resource requirements as long as the required work content is met. Based on the cost of resources units and resource requirements of each activity, there is a corresponding cash flow for the activity. Each phase is ended with a milestone that corresponds to the phase income. We prove that the mode corresponding to the minimum possible duration of each activity is the optimal mode in this problem. We also present a simple optima scheduling procedure to determine the finish time of each activity.
  • M. Karbasian, M. Bashiri, M. Safaei Page 187
    This paper represents a model of strategic programming with limited resources in a complex supply chain. The main goal of the proposed model is to increase efficiency and effectiveness of the supply chain with respect to income increases and cost decreases. Using special objective functions, has guaranteed the lean supply, production, distribution and supplier's selection strategies. Furthermore, it can use for production programming in the supply chain. Moreover, customer satisfaction has also been perceived, by using minimization objective functions of shortage amount and restrictions of maximum allowed shortage. In this model, objective functions have been defined in a way, which directs the supply chain to the lean. Finally, after determining strategies according to objective functions and constraints, the optimal strategies using multi-criteria decision making - ELECTRE process- have been chosen.
  • F. Khaksar-Haghani, N. Javadian, R. Tavakkoli-Moghaddam, A. Baboli, R. Kia Page 199
    This paper presents a novel mixed-integer non-linear programming model for the design of a dynamic cellular manufacturing system (DCMS) based on production planning (PP) decisions and several manufacturing attributes. Such an integrated DCMS model with an extensive coverage of important design features has not been proposed yet and incorporates several manufacturing attributes including alternative process routings, operation sequence, processing time, production volume of parts, purchasing machine, duplicate machines, machine depot, machine capacity, lot splitting, material flow conservation equations, inflation coefficient, cell workload balancing, budget constraints for cell construction and machine procurement, varying number of formed cells, worker capacity, holding inventories and backorders, outsourcing part-operations, warehouse capacity, and cell reconfiguration. The objective of the integrated model is to minimize the total costs of cell construction, cell unemployment, machine overhead and machine processing, part-operations setup and production, outsourcing, backorders, inventory holding, material handling between system and warehouse, intra-cell and inter-cell movements, purchasing new machines, and machine relocation/installation/uninstallation. A comprehensive numerical example taken from the literature is solved by the Lingo software to illustrate the performance of the proposed model in handling the PP decisions and to investigate the incorporated manufacturing attributes in an integrated DCMS.