Sharif University of TechnologyScientia Iranica1026-309822620151201Monitoring multivariate environments using arti cial neural network approach: An overviewMonitoring multivariate environments using arti cial neural network approach: An overview252725473802ENK.AtashgarDepartment of Industrial Engineering, Iran University of Science and Technology, Tehran, P.O. Box 16846-13114, Iran.Journal Article20160104When 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 paperhttps://scientiairanica.sharif.edu/article_3802_65a66729eedb3aa9bd8e547ba31b238a.pdfSharif University of TechnologyScientia Iranica1026-309822620151201A compromise decision-making model based on VIKOR for multi-objective large-scale nonlinear programming problems with a block angular structure under uncertaintyA compromise decision-making model based on VIKOR for multi-objective large-scale nonlinear programming problems with a block angular structure under uncertainty2257125843822ENB.VahdaniFaculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, P.O. Box 3419759811, IranM.SalimiFaculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, P.O. Box 3419759811, IranS.M.MousaviDepartment of Industrial Engineering, College of Engineering, University of Tehran, Tehran, P.O. Box 18151-159, IranJournal Article20160104This 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.https://scientiairanica.sharif.edu/article_3822_b2841f936bf758acedd0268982b8756f.pdfSharif University of TechnologyScientia Iranica1026-309822620151201Analysis of network trust dynamics based on the evolutionary gameAnalysis of network trust dynamics based on the evolutionary game254825573803ENF.LiuSchool of Management Science and Engineering, Shandong Normal University, Ji'nan 250014, China.L.WangSchool of Management Science and Engineering, Shandong Normal University, Ji'nan 250014, ChinaH.JohnsonFaculty of Computer Sciences, Blekinge Institute of Technology, 371 41, Karlskrona, SwedenH.ZhaoDepartment of Computer Science, University of California Davis, One Shields Ave., Davis, CA, 95616, USAJournal Article20160104Trust, 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.https://scientiairanica.sharif.edu/article_3803_be234809e3cc70e0113395469583f9b1.pdfSharif University of TechnologyScientia Iranica1026-309822620151201An inventory model for deteriorating items with inventory-dependent and linear trend demand under trade creditAn inventory model for deteriorating items with inventory-dependent and linear trend demand under trade credit255825703804ENC.F.WuSchool of Economics and Management, Qingdao University of Science & Technology, Qingdao, P.R. ChinaQ.H.ZhaoSchool of Economics and Management, Beihang University, Beijing, P.R. China.Journal Article20160104One 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 implicationhttps://scientiairanica.sharif.edu/article_3804_3ff037568de7565b0b19724f631bb1a2.pdfSharif University of TechnologyScientia Iranica1026-309822620151201On-line cross docking: A general new concept at a container portOn-line cross docking: A general new concept at a container port258525943805ENP.AzimiFaculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.Journal Article20160104Cross 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.https://scientiairanica.sharif.edu/article_3805_eda870b54444c870261b6d0644aa83fd.pdfSharif University of TechnologyScientia Iranica1026-309822620151201Optimal multi-discount selling prices schedule for deteriorating productOptimal multi-discount selling prices schedule for deteriorating product259526033806ENA.A.TaleizadehSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, IranF.SatarianSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, IranA.JamiliSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, IranJournal Article20160104This 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.https://scientiairanica.sharif.edu/article_3806_653177886fa0dc1f067e2bd06f6748e4.pdfSharif University of TechnologyScientia Iranica1026-309822620151201A multi-objective robust optimization model for location-allocation decisions in two-stage supply chain network and solving it with non-dominated sorting ant colony optimizationA multi-objective robust optimization model for location-allocation decisions in two-stage supply chain network and solving it with non-dominated sorting ant colony optimization260426203807ENJ.BagherinejadDepartment of Industrial Engineering, Faculty of Engineering and Technology, Alzahra University, Tehran, IranM.DehghaniDepartment of Industrial Engineering, Faculty of Engineering and Technology, Alzahra University, Tehran, IranJournal Article20160104This 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.https://scientiairanica.sharif.edu/article_3807_5efed9030ecd7bffe0db475e69597aa4.pdfSharif University of TechnologyScientia Iranica1026-309822620151201Closed-form equations for optimal lot sizing in deterministic EOQ models with exchangeable imperfect ACquality itemsClosed-form equations for optimal lot sizing in deterministic EOQ models with exchangeable imperfect quality items262126333808ENM.FarhangiDepartment of Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, IranS.T.A.NiakiDepartment of Industrial Engineering, Sharif University of Technology, Tehran, P.O. Box 11155-9414, Iran.B.Maleki VishkaeiYoung Researchers and Elite Club, Qazvin Branch, Islamic Azad University, Qazvin, IranJournal Article20160104In 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 modelhttps://scientiairanica.sharif.edu/article_3808_732c8480534ab77ac0ad908da23684a0.pdfSharif University of TechnologyScientia Iranica1026-309822620151201Supply chain network design for deteriorating items with discount on transportation costSupply chain network design for deteriorating items with discount on transportation cost263426433809ENM.Hajian HeidaryDepartment of Industrial Engineering, Amirkabir University of Technology, 424 Hafez Avenue, 1591634311, Tehran, IranS.M.T.Fatemi GhomiDepartment of Industrial Engineering, Amirkabir University of Technology, 424 Hafez Avenue, 1591634311, Tehran, IranB.KarimiDepartment of Industrial Engineering, Amirkabir University of Technology, 424 Hafez Avenue, 1591634311, Tehran, IranJournal Article20141119Distribution 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).https://scientiairanica.sharif.edu/article_3809_92e98910f3d511ee8557c13672993947.pdfSharif University of TechnologyScientia Iranica1026-309822620151201Hedging strategies for multi-period portfolio optimizationHedging strategies for multi-period portfolio optimization264426633810ENHamedDavari-ArdakaniDepartment of Industrial Engineering and Management Systems, Amirkabir University of Technology, P.O. Box 15875-4413, Tehran, IranMajidAminnayeriDepartment of Industrial Engineering and Management Systems, Amirkabir University of Technology, P.O. Box 15875-4413, Tehran, IranAbbasSeifiDepartment of Industrial Engineering and Management Systems, Amirkabir University of Technology, P.O. Box 15875-4413, Tehran, IranJournal Article20141202This 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.https://scientiairanica.sharif.edu/article_3810_f3a8794a737eb592f89c290a991caa34.pdfSharif University of TechnologyScientia Iranica1026-309822620151201Computing Centroid of General Type-2 Fuzzy Sets using Constrained Switching AlgorithmComputing Centroid of General Type-2 Fuzzy Sets using Constrained Switching Algorithm266426833811ENAbolfazlDoostparast TorshiziDepartment of Industrial Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran 15875-5513, IranMohammad HosseinFazel ZarandiDepartment of Industrial Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran 15875-5513, IranIsmaeil BurhanTürkşenDepartment of Industrial Engineering, TOBB Economics and Technology University, Sögütözü, Ankara, TurkeyJournal Article20141215Centroid 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.https://scientiairanica.sharif.edu/article_3811_3730e49cf35e4ba23b2625c0355e0a2a.pdfSharif University of TechnologyScientia Iranica1026-309822620151201Some Generalized Einstein Aggregation Operators Based on the Interval-Valued Intuitionistic Fuzzy Numbers and Their Application to Group Decision MakingSome Generalized Einstein Aggregation Operators Based on the Interval-Valued Intuitionistic Fuzzy Numbers and Their Application to Group Decision Making268427013812ENPeideLiuSchool of Economics and Management, Civil Aviation University of China, Tianjin 300300, ChinaYanhuaLiSchool of Economics and Management, Civil Aviation University of China, Tianjin 300300, ChinaYubaoChenSchool of Economics and Management, Civil Aviation University of China, Tianjin 300300, ChinaJournal Article20141028For 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.https://scientiairanica.sharif.edu/article_3812_55c6209e8342b1947d4c222505fe1be3.pdfSharif University of TechnologyScientia Iranica1026-309822620151201Interval-valued Trapezoidal Intuitionistic Fuzzy Generalized Aggregation Operators and Application to Multi-attribute Group Decision MakingInterval-valued Trapezoidal Intuitionistic Fuzzy Generalized Aggregation Operators and Application to Multi-attribute Group Decision Making270227153813ENJiu-yingDONGCollege of Information Technology, Jiangxi University of Finance and Economics, Nanchang, 330013, ChinaShu-pingWANCollege of Statistics, Jiangxi University of Finance and Economics, Nanchang, 330013, ChinaJournal Article20150314Aninterval-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.https://scientiairanica.sharif.edu/article_3813_5312fcc0320d4869301821d7b23e0959.pdfSharif University of TechnologyScientia Iranica1026-309822620151201A Mathematical Model to Evaluate Knowledge in the Knowledge Based-OrganizationsA Mathematical Model to Evaluate Knowledge in the Knowledge Based-Organizations271627213814ENRouhollahBagheriManagement, Faculty of Management and Accounting, Shahid Beheshti University, Daneshju Blvd, Evin Square, Tehran 1983963113, IranAliRezaeianFaculty of Management and Accounting, Shahid Beheshti University, Daneshju Blvd, Evin Square, Tehran 1983963113, IranAmirFazlalyFaculty of Industrial Engineering, Khajehnasir Toosi University, Kaviyan, Tehran 1541849611, IranJournal Article20141011Knowledge 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.https://scientiairanica.sharif.edu/article_3814_bc1573550dbd68e97d205d01bbd65280.pdfSharif University of TechnologyScientia Iranica1026-309822620151201Notes on mathematical formulation and complexity considerations for blocks relocation problemNotes on mathematical formulation and complexity considerations for blocks relocation problem272227283815ENH.EskandariDepartment of Industrial Engineering, Tarbiat Modares University, Tehran, IranE.AzariDepartment of Industrial Engineering, Tarbiat Modares University, Tehran, IranJournal Article20160104In 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.https://scientiairanica.sharif.edu/article_3815_316808799e185d34e57564a8342dd57d.pdf