AJA Command and Staff UniversityJournal of Modern Operations Research2783-14931120210301A GRASP Algorithm for Pickup and Delivery Problem with Time Windows in Vessel Routing ProblemA GRASP Algorithm for Pickup and Delivery Problem with Time Windows in Vessel Routing Problem240078ENShirin Mardanpouruniversity of shirazZiarati Koorushuniversity of shirazJournal Article20201201In a recent study, researchers investigated a class of vessel routing problem and a benchmark suite based on real shipping segments considering incompatibility constraints. These constraints same as pickups and deliveries, cargoes selections, travel times and costs and time windows state considerable challenges for researchers. Considering the literature review on the subject and the frequent resolving of this problem with Adaptive Large Neighborhood Search (ALNS), we proposed a Greedy Randomized Adaptive Search Procedure (GRASP) to solve this problem. The algorithm was tested on 240 available benchmarks. As shown in our experimental results the GRASP outperforms all previous heuristics and generates near-optimal solutions within minutes. These results are noteworthy since we have succeeded to improved 35 large instances of this set.https://www.jmor.ir/article_240078_b4666cc4d0b58feece9c2674fc87062f.pdfAJA Command and Staff UniversityJournal of Modern Operations Research2783-14931120210301Modeling and Simulation of Urban Traffic Network Using Enterprise Dynamics (Case study: the Sabzeh Meydan intersection in Qazvin city)Modeling and Simulation of Urban Traffic Network Using Enterprise Dynamics (Case study: the Sabzeh Meydan intersection in Qazvin city)240076ENArjmand MasoudEbrahimzadeh MajidBarzegar SalmanJournal Article20200903The traffic problem is one of the greatest problems in today's life. Traffic imposes plenty of costs to people, and hence the need to provide solutions to improve it is necessary. In this paper, the traffic problem of one of the busiest passages in Qazvin city, namely Sabzeh Meydan intersection, has been investigated. After introducing the problem definition, the raw data collected from the environment will be explained. Using the data collected, a simulation model of the intersection is created in ED software. Lastly, two scenarios are designed to improve traffic conditions and reduce waiting time. To compare scenarios, both scenarios are modeled via ED. The results proved both scenarios are efficient. Given that the first scenario is costless and immediately applicable, it could be a better option in the short term; however, in the long term, the second scenario could be a positive alternativehttps://www.jmor.ir/article_240076_3207057e31d5d119e5eb703b9052bfec.pdfAJA Command and Staff UniversityJournal of Modern Operations Research2783-14931120210301The extended two-type parameter estimator in linear regression modelThe extended two-type parameter estimator in linear regression model240077ENZeinal AmirJournal Article20200909In this paper, a new two-type parameter estimator is introduced. This estimator is an extension of the two-parameter estimator presented by Özkale and Kaçiranlar [10], which includes the ordinary least squares, the generalized ridge and the generalized Liu estimators, as special cases. Here the performance of this new estimator over the ordinary least squares and two-parameter estimators is , theoretically, evaluated in terms of quadratic bias (QB) and mean squared error matrix (MSEM) criteria, and the optimal biasing parameters are obtained to minimize the scalar mean squared error (MSE). Then a numerical example is given and a simulation study is done to illustrate the theoretical results of the paperhttps://www.jmor.ir/article_240077_70e2a3cfb99938d2280c49ca27771573.pdfAJA Command and Staff UniversityJournal of Modern Operations Research2783-14931120210219Choosing the technology in closed-loop build-to-order supply chainChoosing the technology in closed-loop build-to-order supply chain240079ENEbrahimi MaliheJournal Article20201222Besides the customization, environmental concerns are attracting attention. In this study a closed-loop supply chain in the build-to-order environment is proposed. Build-to-order is a customization system which is without final product inventory. Choosing technology is the other issue considering in this paper. The main benefit of considering the closed-loop model in the build-to-order environment is that the returned products can be disassembled into components which reused. The new mixed integer problem is solved by CPLEX. At last sensitivity analysis is used to examine some parametersAJA Command and Staff UniversityJournal of Modern Operations Research2783-14931120210301The Use of Linear Time Series for Prediction of Congestion Detection in Wireless Sensor NetworksThe Use of Linear Time Series for Prediction of Congestion Detection in Wireless Sensor Networks240066ENRezaei AtiehDepartment of Electrical and Computer Engineering, Faculty of Sepideh Kashani. Birjand Branch. Technical and Vocational University (TVU). South Khorasan. Iran0000-0002-9191-7150Journal Article20200930A Wireless Sensor Network (WSN) is developed with large number of sensor nodes. Packet transfer in this network presents a range of challenges to protocol designers due to resource constrains, limited battery power, processing power, memory and storage capacity of sensor nodes in WSN. The applications that produce high volumes of data which require high transmission rates, may cause congestion in the sensor node and leading to packet loss and impairments in the quality of service (QOS) as well as throughput of networks. If data transmission to the network is not controlled, congestion status can arise and decrease network lifetime. Therefore, we need various congestion detection mechanisms to identify congestion. In this paper, we present a Prediction based Congestion Detection (P-CD) technique in order to identify congestion before congestion occurrence. These techniques use queue length as a parameter to recognition congestion. The introduced technique has better prediction accuracy.https://www.jmor.ir/article_240066_d01f14a032e13d9aece08760597b69c6.pdfAJA Command and Staff UniversityJournal of Modern Operations Research2783-14931120210219Investigating the effective factors in measuring customers' credibility with a combined approach of data mining and multidisciplinary decision making Problemبررسی عوامل موثر در سنجش اعتبار مشتریان با رویکرد ترکیبی داده کاوی و تصمیم گیری چندشاخصه242893ENMaryam Changiz DelivandMasterofIndustrialEngineering,IslamicAzadUniversity,Tehran,IranMohammad Bameni MoghadamProfessor, Department of Statistics, Allameh Tabatabai University, Tehran,IranNader ShamamiHigher Research Institute of War- University of Command and Staff AJAMohammad TaghipourDepartment of Industrial Engineering, Ooj Institute of Higher Education, Qazvin, IranJournal Article20210111In order to provide loans and facilities, banks must be able to identify and classify their customers based on their ability to repay on time. In this way, banks can achieve the least risk and the highest return. This research tries to provide a better opportunity for banks to identify their customers by using two techniques of data mining and multi-indicator decision making. The statistical population of this study is all customers of 98 branches of the National Bank of West Tehran since 1396 (207104 people) who have deposits of more than ten million Rials. In this research, the effective parameters in credit risk are classified according to their importance and using the multi-criteria decision-making method, the customer’s request the facility and the effective factors in measuring the credit of the bank's customers obtained by AHP method include: history of cooperation with the bank. Debt history, loan amount, GPA, customer capital, type of ownership, place of work-living, annual income of the applicant, one-year bank account GPA, loan interest rate, loan term, current capital flow and current capital. Findings show that the average turnover index is the first priority and the applicant's annual income is the last priority.https://www.jmor.ir/article_242893_430d55c353ec113b7e05a95dec52ceaf.pdf