• Home
  • Reza Babazadeh
  • OpenAccess
    • List of Articles Reza Babazadeh

      • Open Access Article

        1 - A metaheuristic algorithm for optimizing strategic and tactical decisions in a logistics network design problem
        رضا بابازاده
        Todays, industries are seeking the ways to improve their competitiveness and responsiveness in order to achieve the most share of markets and customer satisfaction. Optimization of strategic and tactical decisions in a logistics network would improve total performance o More
        Todays, industries are seeking the ways to improve their competitiveness and responsiveness in order to achieve the most share of markets and customer satisfaction. Optimization of strategic and tactical decisions in a logistics network would improve total performance of the supply chain in a long term planning horizon. This paper presents a Mixed-integer linear programming (MILP) model to optimize logistics networks under real limitations such as demand, capacity, and budget constraints. Due to NP-hard nature of the proposed model a Differential Evolutionary (DE) algorithm is proposed to solve the large sizes of the presented model in reasonable time. Finally, the computational results obtained through the DE algorithm are compared with the solutions obtained by GAMS optimization software. The results reveal that the proposed methodology is an efficient tool to optimize large scale logistics networks. Manuscript profile
      • Open Access Article

        2 - Efficiency Evaluation of Railway Freight Stations by Using DEA Approach
        Davoud Haghighi رضا بابازاده
        Railway freight stations roles as points in which traffic processes can be merged and diverged are of paramount importance. Numerous activities such as train formation, alighting and interchanging, technical checks are also done at these points. Due to the great importa More
        Railway freight stations roles as points in which traffic processes can be merged and diverged are of paramount importance. Numerous activities such as train formation, alighting and interchanging, technical checks are also done at these points. Due to the great importance of using railway infrastructures and rolling stocks facilities efficiently, the efficiency studies in this area are considered as a demanding task more than ever. Therefore, we implement a methodology based on data envelopment analysis to address this issue. The suggested methodology in this research can be used for measuring the efficiency of railway freight stations and ranking them by using DEA and Anderson & Peterson methods. This methodology can be used for analyzing the relative ‘technical efficiency’ of railway freight stations to manage train stops regarding the current station capacity. We applied this model in a case study of the 12 busiest train stations in Isfahan railway to measure and rank their efficiency and assess the effect of traffic type on the results by using robust regression. Manuscript profile
      • Open Access Article

        3 - An Artificial Neural Network Method to Predict the COVID-19 Cases in Iran
        Meisam Shamsi رضا بابازاده Mohsen Varmazyar
        The sudden emergence of a Coronavirus and its rapid spread due to the globalization factors, especially the airline network, provoked the reaction of countries. Governments attempt to use all available means, including prediction methods, to control the spread of the Co More
        The sudden emergence of a Coronavirus and its rapid spread due to the globalization factors, especially the airline network, provoked the reaction of countries. Governments attempt to use all available means, including prediction methods, to control the spread of the Coronavirus. In this article, we have developed various models based on artificial neural networks, including multi-layer perceptron, radial basis function, and adaptive-network-based fuzzy inference system with different learning algorithms, transfer functions, membership functions, hidden layers, hidden neurons, and kernels. We have identified five factors influencing the Coronavirus outbreak based on the Pearson correlation coefficient approach. These factors are gasoline consumption, internet pressure, number of wedding ceremonies, online transactions, and mask consumption. The accuracy of the developed models is identified by calculating three types of statistical errors, including root mean square error, mean absolute error, and mean absolute percentage error. The results show that the radial basis function model predicts the number of Covid-19 cases for the one month (mid-term) with an accuracy of over 97%. This study provides an efficient approach to predict the number of COVID-19 cases which help policymakers to make strategic decisions, including closing borders, designing supply chains for medical and health equipment, and enacting new laws. Manuscript profile