فهرست مطالب

Scientia Iranica
Volume:22 Issue: 6, 2015

  • Transactions E: Industrial Engineering
  • تاریخ انتشار: 1394/10/28
  • تعداد عناوین: 15
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  • K. Atashgar Page 2527
    When a process shifts to an out-of-control condition, a search should be initiated to identify and eliminate the special cause(s) manifested to the technical speci cation(s) of the process. In the case of a process (or a product) involving several correlated technical speci cations, analyzing the joint e ects of the correlated speci cations is more complicated compared to a process involving only one technical speci cation. Most real cases refer to processes involving more than one variable. The complexity of a solution to monitor the condition of these processes, estimate the change point and identify further knowledge leading to root-cause analysis motivated researchers to develop solutions based on Arti cial Neural Networks (ANN). This paper provides, analytically, a comprehensive literature review on monitoring multivariate processes approaching arti cial neural networks. Analysis of the strength and weakness of the proposed schemes, along with comparing their capabilities and properties,, are also considered. Some opportunities for new researches into monitoring multivariate environments are provided in this paper.
    Keywords: Arti cial neural network, Multivariate process, Diagnostic analysis, Change point
  • F. Liu|L. Wang, H. Johnson, H. Zhao Page 2548
    Trust, as a multi-disciplinary research domain, is of high importance in the area of network security and it has increasingly become an important mechanism to solve the issues of distributed network security. Trust is also an e ective mechanism to simplify complex society, and is the source to promote personal or social cooperation. From the perspective of network ecological evolution, we propose the model of the P2P Social Ecological Network. Based on game theory, we also put forward network trust dynamics and network eco-evolution by analysis of network trust and the development of the dynamics model. In this article, we further analyze the dynamic equation, and the evolutionary trend of the trust relationship between nodes using the replicator dynamics principle. Finally, we reveal the law of trust evolution dynamics, and the simulation results clearly describe that the dynamics of trust can be e ective in promoting the stability and evolution of networks.
    Keywords: Trust, Trust dynamics, Game theory, Evolutionary game
  • C.F. Wu, Q.H. Zhao Page 2558
    One of the important issues in inventory management is permissible delay in payments. Previous inventory lot-size models allowing permissible delay in payments implicitly assumed that the demand rate is constant and inventory-dependent. However, this paper, unlike most existing models, this paper develops an Economic Order Quantity (EOQ) model for deteriorating items with a current inventory-dependent and linearly increasing time-varying demand under trade credit, which ts a more general inventory feature. An effcient solution procedure is shown to determine the optimal replenishment cycle of the model. Furthermore, this study deduces some previously published results as special cases of the proposed model. Finally, numerical examples are presented to illustrate the optimization procedure, and a sensitivity analysis is performed for changes in the parameters to obtain important and relevant ndings on managerial implication.
    Keywords: Inventory, dependent, linear trend demand, Economic Order Quantity (EOQ), Trade credit, Deteriorating items, Permissible delay in payments
  • B. Vahdani, M. Salimi, S.M. Mousavi Page 2571
    This paper proposes a model on the basis of VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methodology as a compromised method to solve the Multi-Objective Large-Scale Nonlinear Programming (MOLSNLP) problems with block angular structure involving fuzzy coeffcients. The proposed method is introduced for solving large scale nonlinear programming in fuzzy environment for rst time. The problem involves fuzzy coeffients in both objective functions and constraints. In this method, an aggregating function developed from LP- metric is based on the particular measure of closeness «to the ideal» solution. The solution process is composed of two steps: First, the decomposition algorithm is utilized to reduce the q-dimensional objective space into a one-dimensional space. Then a multi-objective identical crisp non-linear programming is derived from each fuzzy non-linear model for solving the problem. Second, for nding the nal solution, a single-objective large-scale nonlinear programming problem is solved. In order to justify the proposed method, an illustrative example is presented and followed by description of the sensitivity analysis.
    Keywords: VlseKriterijumska_Optimizacija I Kompromisno Resenje (VIKOR)_Multiple Criteria Decision Making (MCDM)_Multi_Objective Decision Making (MODM)_Multi_Objective Large_Scale Nonlinear Programming (MOLSNLP)_Block angular structure
  • P. Azimi Page 2585
    Cross docking is one of the innovation product distribution strategies for transhipment of time-sensitive products in distribution centers which has absorbed a lot of attention in the last 10 years. The current study develops a new concept named on-line docking«in an actual container port which is the main contribution of the research. In the model, some previous simpli cations were removed from the model using optimization via simulation technique, and also new decision variables were introduced to control the system. The objective function is to minimize the average annual system costs by assigning the best number of inbound-outbound docks and the fleet size for the internal transportations. To do so, all information was taken from an actual container port system and the model was built in the simulation software and then it was optimized via a meta-heuristic algorithm. The computational results show the effciency of the proposed approach in real world applications.
    Keywords: Discrete event simulation, Cross docking terminals, Optimization via simulation, Genetic algorithm
  • A.A. Taleizadeh, F. Satarian, A. Jamili Page 2595
    This paper investigates optimal multi discount price and order quantity for deteriorating product. We initially consider a time dependent demand function with two scenarios including positive exponential for the rst interval and negative exponential for the second one, due to the obsolescent characteristic, without any exogenous factor. Then, we study the e ect of changing selling price as an exogenous factor causing increase in demand. Finally, optimization model is formulated and the closed form solutions of the optimal prices are gained.
    Keywords: Pricing, Multi discount selling prices, Economic order quantity, Deterioration
  • J. Bagherinejad, M. Dehghani Page 2604
    This study proposes a new, robust multi-objective model for capacitated multivehicle allocation of customers to potential Distribution Centers (DCs) under uncertain environment. Uncertainty is de ned by discrete scenarios on demands where occurrence probability of each scenario is known. The optimization objectives are to minimize transit time and total cost, including opening cost, assumed for opening potential DCs and shipping cost from DCs to the customers, where considering di erent types of vehicles leads to a more realistic model and causes more con ict in these two objectives. A swarm intelligencebased algorithm named Non-dominated Sorting Ant Colony Optimization (NSACO) is used as the optimization tool. The proposed methodology is based on a new variant of Ant Colony Optimization (ACO) customized in multi-objective optimization problem of this research. For ensuring the authenticity of the proposed method, the computational results are compared with those obtained by NSGA-II. Results show the advantages and the e ectiveness of the used method in reporting the optimal Pareto front of the proposed model. Moreover, the optimal solutions of the robust optimization model are insensitive to the disturbance of parameters under di erent scenarios, thus the risk of decision can be eff ectively reduced.
    Keywords: Robust multiobjective optimization, Location, allocation, Multi, vehicle, Uncertainty, Non, dominated sorting ant colony optimization, NSGA, II
  • M. Farhangi, S.T.A. Niaki, B. Maleki Vishkaei Page 2621
    In this paper, the optimal lot size for batches with exchangeable imperfect items is derived where the delay time for the exchange process depends on the quantity of imperfect items. This delay in exchange may or may not lead into shortage. The initial received lot is 100% screened. After the screening process, an order to exchange defective products takes place. The imperfect items are held in buyer''s warehouse until the arrival of the exchange lot from the supplier for which, after another 100% screening process, imperfect items are sold at a lower price in a single batch. Two possible situations in which 1) there will not be any shortage, and 2) there will be a shortage that is ful lled before the end of the replenishment cycle, are investigated. Proper mathematical models are developed and closed-form formulae are derived. Numerical examples are provided not only to demonstrate application of the proposed model, but also to analyze and compare the results obtained employing the proposed model and the ones gained using the classical economic order quantity model.
    Keywords: Inventory, Economic order quantity, 100% screening, Imperfect items, Exchangeable items, Shortage
  • M. Hajian Heidary, S.M.T. Fatemi Ghomi, B. Karimi Page 2634
    Distribution of deteriorating items is different from other items. This issue leads distributors to transport with lower volumes. On the other hand, one of the mechanisms that attract buyers to purchase items is discount; but a larger amount of order has a lower price for one item but has a higher risk of deterioration. Despite the importance of issue, previous researches on deteriorating items did not consider discount conditions in designing supply chain network. Hence, in this paper, balancing between the cost of ordering and the cost of deterioration with consideration of discount through a new model is studied. The problem is solved for numerical examples with an improved meta-heuristic composed of simulated annealing (SA) and genetic algorithm (GA) and results are reported. Furthermore, a heuristic method for small scale problems is represented and compared with the introduced algorithm to analyze the performance of method. Finally, results show a significant difference between the costs of the models (with discount and without it).
    Keywords: Supply chain network design, Deteriorating items, Discount, improved meta, heuristic algorithm
  • Hamed Davari, Ardakani, Majid Aminnayeri, Abbas Seifi Page 2644
    This paper develops a multi-period portfolio optimization model that utilizes hedging decisions in a dynamic setting. In this regard, a portfolio of options and underlying stocks is constructed and different time-varying Greek letters are utilized to mitigate the market risk. The presented model considers rebalancing decisions during the planning horizon. It assumes an investor aiming to maximize his/her wealth at the end of the planning horizon, while controlling the investor’s regret during the planning horizon. The uncertainty of asset prices is represented in terms of a scenario tree. In addition, a scenario generation method is presented that characterizes the temporal correlations and dependence structure of asset returns. Also, it preserves marginal distributions of asset returns. To investigate the effect of hedging strategies, we first implement the scenario generation method on a set of stocks selected from New York Stock Exchange (NYSE). Numerical results show the high performance of the scenario generation method. Then, the multi-period portfolio optimization model is implemented via the generated scenario tree. Results show that incorporation of options remarkably reduces the investor’s risk. Finally, different hedging strategies are assessed by imposing bounds on the values of Greek letters and a discussion about numerical results is presented.
    Keywords: Multi, period portfolio optimization, European options, Hedging strategies, Greek letters, Scenario generation
  • Abolfazl Doostparast Torshizi, Mohammad Hossein Faze, Zarandi, Ismaeil Burhan TÜrkŞ, En Page 2664
    Centroid of a general type-2 fuzzy sets can be used as a measure of uncertainty in highly uncertain environments. Computing centroid of general type-2 fuzzy sets has received an increasing research attention during recent years. Although computation complexity of such sets is higher than interval type-2 fuzzy sets but with the advent of new representation techniques, e.g., α-planes and z-slices, computation efforts needed to deal with general type-2 fuzzy sets has decremented. A very first method to calculate the centroid of a general type-2 fuzzy set was to use Karnik-Mendel algorithm on each α-plane, independently. Because of iterative nature of this method, running time in this approach is rather high. To tackle such drawback, several emerging algorithms such as Sampling method, Centroid-Flow algorithm and, recently, Monotone Centroid-Flow algorithm have been proposed. The aim of this paper is to present a new method to calculate centroid intervals of each α-plane independently while reducing convergence time compared with other algorithms like iterative use of Karnik-Mendel algorithm on each α-plane. The proposed approach is based on estimating an initial switch point for each α-plane. Exhaustive computations demonstrate that the proposed method is considerably faster than independent implementation of existing iterative methods on each α-plane.
    Keywords: General type, 2 fuzzy sets, Constrained Switching (CS) algorithm, type reduction, α plane representation, enhanced Karnik, Mendel (KM) algorithms
  • Peide Liu, Yanhua Li, Yubao Chen Page 2684
    For the multiple attribute group decision making (MAGDM) problems whereattribute values arethe interval-valued intuitionistic fuzzy numbers (IVIFNs), the group decision making method based on some generalized Einstein aggregation operators is developed. Firstly, interval-valued intuitionistic fuzzy generalized Einstein weighted averaging (IVIFGEWA) operator, interval-valued intuitionistic fuzzy generalized Einstein ordered weighted averaging (IVIFGEOWA) operator, and interval-valued intuitionistic fuzzy generalized Einstein hybrid weighted averaging (IVIFGEHWA) operator, were proposed. Some general properties of these operators, such as idempotency, commutativity, monotonicity and boundedness, were discussed, and some special cases in these operators were analyzed. Furthermore, the method for MAGDM problems based on these operators was developed, and the operational processes were illustrated in detail. Finally, an illustrative example is given to show the decision steps of the proposed methods and to demonstrate their and effectiveness.
    Keywords: Group decision, making, interval, valued intuitionistic fuzzy numbers, Einstein aggregation operators, multiple attribute decision making
  • Jiu, Ying Dong, Shu, Ping Wan Page 2702
    Aninterval-valued trapezoidal intuitionistic fuzzy number (IVTrIFN) is a special case of an intuitionistic fuzzy set (IFS), which is defined on the real number set. From a viewpoint of geometric, the expectation and expectant score of an IVTrIFN are defined by using the notion of barycenter, and a new method is developed to rank IVTrIFNs. Hereby, some generalized aggregation operators of IVTrIFNs are defined, including the generalized ordered weighted averaging operator of IVTrIFNs and the generalized hybrid weighted averaging operator of IVTrIFNs, and employed to solve multi-attribute group decision making problems with IVTrIFNs. Through using the weighted average operator of IVTrIFNs, the attribute values of alternatives are integrated into the individual comprehensiveratings, which are further aggregated into the collective one by the generalized hybrid weighted averaging operator of IVTrIFNs. The ranking orders of alternatives are then generated according to the expectation and expectant score of the collective comprehensiveratings of alternatives. A numerical example is examined to demonstrate applicability and implementation process of the decision method proposed in this paper.
    Keywords: Multi, attribute group decision making, interval, valued trapezoidal intuitionistic fuzzy number, generalized aggregation operator, barycenter
  • Rouhollah Bagheri, Ali Rezaeian|Amir Fazlaly Page 2716
    Knowledge and its intangible appurtenances have not only have resulted in movement in various businesses, but also they have been nowadays viewed as whole or a part of products of distributors companies as well as service and military organizations. In recent years, estimation of knowledge level in organizations and industry companies has attracted considerable attentions. Contrary to a lot of prevalent models used for measuring efficiency, data envelopment analysis (DEA) can take into account multiple inputs and outputs. In this regard, DEA was traditionally applied with crisp inputs and outputs, while in practical cases. We need to estimate organization efficiency in a different situation in which we have to deal with fuzzy or imprecise data. The aim of this paper is to present a DEA employing fuzzy input and output data toward assessing knowledge level established in a knowledge based-organization in various time intervals. In this case, the organization is able to define some areas in which it can improve its established knowledge level.
    Keywords: knowledge management, data envelopment analysis, mathematical model, BCC model, Fuzzy set
  • H. Eskandari, E. Azari Page 2722
    In a recent paper, Caserta et al. [M. Caserta, S. Schwarze, and S. Vo. A mathematical formulation and complexity considerations for the blocks relocation problem«, European Journal of Operational Research, 219, pp. 96-104 (2012)] proposed two mathematical models for the blocks relocation problem. Because of the complexity of their rst model, called BRP-I, they employed a simplifying assumption and introduced a relatively fast model, called BRP-II, to solve medium-sized instances. In this paper, it is rst proven that the BRP-II model is incorrect. Then, the corrected and improved formulation of BRP-II, called BRP2c and BRP2ci, respectively, are presented. By correcting a constraint in BRP-II, the reported optimal solution is either corrected or improved in many instances. Also, it is proven that some results of BRP-II reported by Caserta et al. are incorrect. Incorporating some new cut constraints into BRP2ci, the computational time of solving instances is decreased 25 times, on average.
    Keywords: Logistics, Blocks relocation problem, Integer programming, Cut constraints, Optimization