Sharif University of TechnologyScientia Iranica1026-309825420180801Bi-objective scheduling for the re-entrant hybrid flow shop with learning effect and setup times22332253445110.24200/sci.2017.4451ENS.M.MousaviDepartment of Industrial Engineering, Mazandaran University of Science and Technology, Babol, IranI.MahdaviDepartment of Industrial Engineering, Mazandaran University of Science and Technology, Babol, IranJ.RezaeianDepartment of Industrial Engineering, Mazandaran University of Science and Technology, Babol, IranM.ZandiehDepartment of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, G. C., Tehran, IranJournal Article20151124The production scheduling problem in hybrid flow shops is a complex combinatorial optimization problem observed in many real-world applications. The standard hybrid flow shop problem involves often unrealistic assumptions. In order to address the realistic assumptions, four additional traits were added to the proposed problem. These include re-entrant line, setup times, position-dependent learning effects, and the consideration of maximum completion time together with total tardiness as objective function. Since the proposed problem is non-deterministic polynomial-time (NP)-hard, a meta-heuristic algorithm is proposed as the solution procedure. The solution procedure is categorized as an a priori approach. To show the efficiency and effectiveness of the proposed algorithm, computational experiments were done on various test problems. Computational results show that the proposed algorithm can obtain an effective and appropriate solution quality for our investigated problemSharif University of TechnologyScientia Iranica1026-309825420180801Pricing and advertising decisions in a dominant-retailer supply chain: A multi-follower bi-level programming approach22542266453510.24200/sci.2017.4535ENMaryamMokhlesianFaculty of Industrial & Systems Engineering, Tarbiat Modares University, Tehran, IranSeyed HessameddinZegordiFaculty of Industrial & Systems Engineering, Tarbiat Modares University, Tehran, IranJournal Article20160101Pricing and advertising is one of the most important decisions in each supply chain especially in the competitive environment. In the previous studies, this is as a centralized decision. However, if each channel member makes its decision independently, the utility of all members is optimized. In such decentralized situations, the channel members may have different market power that they influence on the other members’ decisions. These issues can modeled through leader-follower Stackelberg game or bi-level programming. This study investigates coordination of pricing and cooperative advertising in a two-stage supply chain consisting of one dominant-retailer and multiple competitive manufactures which produce several perishable and substitutable products. This paper aims to determine pricing and cooperative advertising decisions expenditure as well as the amount of manufacturers’ production or retailer’s purchase such that utility of all members is met. Hence, the problem is modeled as a multi-follower bi-level programming problem. Since it is proved that the model is NP-hard, the proposed model is solved through simulated annealing. A numerical example is used to show the impact of demand’s variations on the members’ decisions.Sharif University of TechnologyScientia Iranica1026-309825419991130Optimization of multi-response problems with continuous functional responses by considering dispersion effects22672281445810.24200/sci.2017.4458ENMohammad HasanBakhtiarifarDepartment of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, IranMahdiBashiriDepartment of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran0000-0002-5448-1773AmirhosseinAmiriDepartment of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran0000-0002-2385-8910Journal Article19991130In some processes, quality of a product should be characterized by functional relationships between response variables and a signal factor. Hence the traditional methods cannot be used to find the optimum solution. In this paper, we propose a method which considers two different dispersion effects, i.e. in domain and between replicates variations in the functional responses. Besides, we propose an integral based measure to find the deviation from tSharif University of TechnologyScientia Iranica1026-309825420180801Optimizing the number of outbound doors in the crossdock based on a new queuing system with the assumption of beta arrival time22822296445210.24200/sci.2017.4452ENA.Motaghedi-LarijaniAmirkabir University of Technology, Tehran, IranM.AminnayeriAmirkabir University of Technology, Tehran, IranJournal Article20160222Crossdocking is one of the supply chain strategies that can reduce transportation and inventory costs. Many studies are conducted the problem of crossdocking by considering various characteristics of crossdocks. In this paper, a queuing model is proposed in order to optimize the number of outbound doors based on minimizing the total costs including the costs of adding a new outbound door and the expected waiting time of customers. The total number of trucks arriving for service is constant. Trucks arrive to outbound doors of the crossdock within a specified time window. Arrival times of trucks follow a beta distribution and customers to be served based on first in first out policy (FIFO). Since, the total number of customers as well as the time of arrivals are finite, the steady state distribution for the long run of the system is inapplicable. Instead, based on conditional joint probabilities, order statistics along with the Bayes theorem we calculate the total expected waiting time.Sharif University of TechnologyScientia Iranica1026-309825420180801Robust-fuzzy model for supplier selection under uncertainty: An application to the automobile industry22972311445610.24200/sci.2017.4456ENMasoodRabiehDepartment of Industrial Management, Shahid Beheshti University, Tehran, IranMohammadModarresDepartment of Industrial Engineering, Sharif University of Technology, Tehran, IranAdelAzarDepartment of Industrial Management, Tarbiat Modares University, Tehran, IranJournal Article20160303This paper proposes an innovative robust-fuzzy method for multi-objective, multi-period supplier selection problem under multiple uncertainties. This approach integrates robust optimization and fuzzy programming. Uncertain parameters are modeled as random variables that take value within a symmetrical interval. However, due to the complexity or ambiguity of some real world problems and specially the nature of some of the available input data, the length of interval is also highly uncertain. This ambiguity motivated us to present a new approach, which can be applicable to multiple uncertainties conditions. Thus, in our approach the half-length of these intervals is also represented by fuzzy membership function. We develop a model and a solution approach to select suppliers by considering risk. The proposed method is applied to a real case of supplier selection in automobile industry under uncertainty and ambiguity conditions. To verify the proposed model, we evaluated the results by simulation technique and compared values of objective function under different scenarios.Sharif University of TechnologyScientia Iranica1026-309825420180801A cluster-based emergency vehicle routing problem in disaster with reliability23122330445010.24200/sci.2017.4450ENZahraGharibDepartment of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, IranAliBozorgi-AmiriSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, IranRezaTavakkoli-MoghaddamSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, IranEsmaeilNajafiDepartment of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, IranJournal Article20160720In the event of natural disasters, relief distribution is the most challenging problem of emergency transportation. What is important in response to disaster is victims’ relief in disaster areas with the quick distribution of vital commodity. In this regard, damage to infrastructure (e.g., roads) can make trouble in designing a distribution network. So, this paper considers a problem using a three-stage approach. In the first stage, pre-processing of model inputs is done through an artificial neural fuzzy inference system (ANFIS) followed by investigating the safest route for each cluster using of decision-making techniques and graph theory. In the second stage, a heterogeneous multi-depots multi-mode vehicle routing problem is formulated for minimizing the transportation time and maximize the reliability. Finally, since the routing problem is NP-hard, two multi-objective meta-heuristic algorithms, namely non-dominated sorting genetic algorithm (NSGA-II) and multi-objective firefly algorithm (MOFA), are proposed to obtain the optimal solution and compared their performance through a set of randomly generated test problems. The results show that for this routing problem, the MOFF gives better solutions in comparison to NSGA-II and performs well in terms of accuracy and solution time.Sharif University of TechnologyScientia Iranica1026-309825420180801Multi-machine economic production quantity for items with scrapped and rework with shortages and allocation decisions23312346445310.24200/sci.2017.4453ENAmir HosseinNobilFaculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran0000-0003-4769-4460Amir HoseinAfshar SedighDepartment of Information Science, University of Otago, Dunedin, New ZealandLeopoldo EduardoCárdenas-BarrónSchool of Engineering and Sciences
Tecnológico de Monterrey
Ave. E. Garza Sada 2501 Sur, C.P. 64849, Monterrey, Nuevo León, MéxicoJournal Article20160810This study considers a multi-product multi-machine economic production quantity inventory problem in an imperfect production system that produces two types of defective items: items that require rework and scrapped items. The shortage is allowed and fully backordered. The scrapped items are disposed with a disposal cost and the rework is done at the end of the normal production period. Moreover, a potential set of available machines for utilization is considered such that each has a specific production rate per item. Each machine has its own utilization cost, setup time and production rate per item. The considered constraints are initial capital to utilize machines and production floor space. The proposed inventory model is a mixed integer non-linear programing mathematical model. The problem is solved using a bi-level approach, first, the set of machines to be utilized and the production allocation of items on each machine are obtained thru a genetic algorithm. Then, using the convexity attribute of the second level problem the optimum cycle length per machine is determined. The proposed hybrid genetic algorithm outperformed conventional genetic algorithm and a GAMS solver, considering solution quality and solving time. Finally, a sensitivity analysis is also given.Sharif University of TechnologyScientia Iranica1026-309825420180801Inventory of complementary products with stock-dependent demand under vendor-managed inventory with consignment policy23472360445710.24200/sci.2017.4457ENM.HemmatiDepartment 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, Iran0000-0003-4363-994XMohsen S.SajadiehDepartment of Industrial Engineering, Amirkabir University of Technology, 424 Hafez avenue, 1591634311, Tehran, IranJournal Article20160923This paper proposes an integrated two-stage model, which consists of one vendor and one buyer for two complementary products. The vendor produces two types of products and delivers them to the buyer in distinct batches. Buyer stocks items in the warehouse and on the shelf. The demand for each product is sensitive to stock levels of both products. A vendor managed inventory with consignment stock policy is considered. The number of shipments and replenishment lot sizes are jointly determined as decision variables in such a way that total profit is maximized. The numerical study shows that as complementary rate increases, the quantity of transfers and demand of both products increase. Hence, ignoring the complementation between products leads to some customers lost.Sharif University of TechnologyScientia Iranica1026-309825420180801Efficient ratio-type estimators of finite population mean based on correlation coefficient23612372445510.24200/sci.2017.4455ENMuhammadIrfanDepartment of Mathematics, Institute of Statistics, Zhejiang University, Hangzhou 310027, ChinaMariaJavedDepartment of Mathematics, Institute of Statistics, Zhejiang University, Hangzhou 310027 ChinaZhengyanLinDepartment of Mathematics, Institute of Statistics, Zhejiang University, Hangzhou 310027 China.Journal Article20160928We proposed efficient families of ratio-type estimators to estimate finite population mean using known correlation coefficient between study variable and auxiliary variable by adopting Singh and Tailor [Singh, H. P., and Tailor, R. “Use of known correlation coefficient in estimating the finite population means”, Statistics in Transition, 6(4), pp. 555-560 (2003)] estimator and Kadilar and Cingi [Kadilar, C., and Cingi, H. “An improvement in estimating the population mean by using the correlation coefficient”, Hacettepe Journal of Mathematics and Statistics, 35(1) pp. 103-109. (2006a)] class of estimators in simple random sampling without replacement. The newly proposed estimators behave efficiently as compared to the common unbiased estimator, traditional ratio estimator and the other competing estimators. Bias, mean squared error and minimum mean squared error of the proposed ratio-type estimators are derived. Moreover, theoretically findings are proved with cooperation of two real data sets.<br /> <strong> </strong>Sharif University of TechnologyScientia Iranica1026-309825420180801A novel correlation coefficient of intuitionistic fuzzysets based on the connection number of set pair analysis and its application23732388445410.24200/sci.2017.4454ENHarishGargSchool of Mathematics, Thapar University Patiala 147004, Punjab, India0000-0001-9099-8422KamalKumarSchool of Mathematics, Thapar University Patiala 147004, Punjab, IndiaJournal Article20161101Set pair analysis (SPA) is an updated theory for dealing with the uncertainty, which overlaps the other<br />theories of uncertainty such as probability, vague, fuzzy and intuitionistic fuzzy set (IFS). Considering the<br />fact that the correlation coecient plays an important role during the decision-making process, in this paper,<br />after pointing out the weakness of the existing correlation coecients between the IFSs, we propose a novel<br />correlation coecient and weighted correlation coecients formulation to measure the relative strength of the<br />dierent IFSs. For it, rstly corresponding to each intuitionistic fuzzy number, the connection number of the<br />SPA theory has been formulated in the form of the degree of identity, discrepancy and contrary and then<br />based on its, a novel correlation coecient measures have been dened. Pairs of identity, discrepancy and<br />contrary of the connection number have been taken as a vector representation during the formulation. Lastly,<br />a decision-making approach based on the proposed measures has been presented which has been illustrated<br />by two numerical examples in pattern recognition and medical diagnosis.