Journal of Advances in Industrial Engineering
Volume:55 Issue: 3, Summer 2021

transportation planners have always paid special attention to rail transport and its development due to its high capacity and low shipping costs. Two solutions apply to the development of rail transit 1. deployment of new infrastructure and 2. improvement of existing conditions and procedures. This study proposes a dynamic binary mathematical programming model to formulate the existing rail freight procedures. Also, the current study proposes two simulation scenarios (First Come First Served and Shortest Processing Time) for solving mathematical programming. Two different perspectives are considered 1. maximize the railway of the Islamic Republic of Iran (RAI) revenue and 2. maximize the rail transport companies' benefit. The main constraints are the loading /unloading capacity of stations, rail line capacity, and the capacity of locomotives to make up trains. Also, this study assumes that freight demand, travel time, and unloading /loading time are stochastic variables. In summary, this paper argued that the SPT strategy requires fewer wagons than FCFS, while the average productivity in SPT mode increases approximately by one unit, and unmet demand decreases. The results also show that the revenue of the rail freight companies in SPT strategy is more than FCFS strategy in all scenarios. Comparing the results of the models with/without taking wagons maintenance into account shows that if the maintenance of wagons is considered, the numbers of required wagons will increase, productivity will decrease, average revenue per wagon of RAI and the average profit of rail freight transport companies will reduce.

In the present research, stock returns were predicted using the Bayesian model approach in Tehran Securities Exchange. Therefore, the research hypothesis that based on Bayesian method has higher accuracy in predicting returns than autoregressive models was developed and tested. In order to examine the hypothesis, information related to the index of 30 selected industries in the Tehran Stock Exchange during the period from 2017/03/25 to 2020/08/24 was used. The index return was predicted based on two methods for 30 out-of-sample data. First autoregressive models were fitted on returns of each index and then the next 30 days of returns were predicted based on these models. Then after identifying the optimal model lags through the Bayesian Model Averaging method, autoregressive models were fitted with the optimal lags and the next 30 days predictions were obtained under this method.In order to compare the accuracy of the methods in predicting the return, RMSE and MAE criteria were used, and the values of these error criteria were compared using Wilcoxon Nonparametric Pairwise comparison tests.The results showed that Bayesian method leads to increase the accuracy of model prediction in out of sample data.

Statistical variables are divided into two categories: nominal and ordinal, both of which have many uses. In some statistical process monitoring applications, quality of a process or product is described by more than one ordinal quality characteristics called ordinal multivariate process. To show the relationship between these variables, an ordinal contingency table is used and modeled with ordinal log-linear model. In our manuscript, two new statistics including simple ordinal categorical and Generalized-p are developed for Phase II monitoring the ordinal log-linear model based processes. Performance of the proposed statistics are evaluated by using some simulation studies and a real numerical example. Results show the superiority of simple ordinal categorical based control chart. In addition, performance of these statistics is accessed through a sensitivity analysis on the size of the rows and columns of the contingency table. Meanwhile, a sensitivity analysis with three and four categorical factors is performed and similar results are obtained.

Nowadays, the proper safety and health assessment in hazardous waste recycling organizations has become an encouraging subject, mainly in developing countries. An assessment of hazardous waste recycling (HWR) facility choice can be introduced as a complex multi-criteria decision-making (MCDM) problem that contains many alternatives solutions with incompatible tangible and intangible indexes. This paper proposes a new decision method based on MCDM approach under intuitionistic fuzzy (IF) environment. The proposed approach is separated from association operators of IFSs; Furthermore, a few modifications in the common complex proportional evaluation method and a procedure for obtaining indexes of weights are introduced. This paper is constructed based on the entropy method to compute weights of criteria, the similarity measure to obtain the decision-makers (DMs)’ weights under IF conditions. Afterward, a new ranking method is introduced based on a new similarity ideal solution method. The major advantage of the suggested new ranking approach is to achieve the best alternatives compared to DMs’ decisions as well as the effects of evaluation values. Hence, the proposed model is a more generalized and proper demonstration to take the real-life fuzziness than the previous studies carefully. Recently, increasing challenges for environmental subjects needs the assessment of HWR facility selection concerning various indexes; so, the feasible problem is given based on a real case study of HWR facility selection, which proves the validity and feasibility of the proposed method. Eventually, a comparative analysis is presented to verify the performance of the proposed method by comparing with IF-CODAS approach.

Mining industry is taken into consideration due to its significant role in the economic growth of developing countries. Moreover, stone quarries have great effects on other industry sectors such as building and production. Thus, this research presents a three-objective multi-period multi-product mixed-integer quadratic programming problem to optimize a sustainable stone supply chain network design. Maximizing total profit as an economic aspect, minimizing sound pollution as a social aspect, and minimizing dust pollution as an environmental aspect of sustainability are considered simultaneously in this paper for the first time. Furthermore, stone pricing is considered in this paper through a price-based demand. An -constraint approach is utilized to solve the multi-objective model and achieve the non-dominated solutions. A real case study on Iranian stone quarries is analyzed to show the applicability of the addressed model. Finally, the managerial insights are presented as guidance to the government and managers for better decisions in the mentioned supply chain. The results show the great potential of installing quarries in the center of Iran geographically and that Razavi Khorasan is the best area for exporting stones.

In today's world, communication between different communities is a must. One of the mechanisms of communication between humans has been the use of the bridge industry. Bridges can have an impact on the communication between two sections or two different geographical areas. In this study, it was found that the use of bridges includes two operations of bridge construction or bridge reconstruction. Due to resource constraints and issues related to the location of the new area and the exorbitant construction costs, the reconstruction of old bridges is considered a suitable approach. Therefore, some important candidate factors are existed for reconstruction of old bridges that should rank to help managers for get an efficient decision. Meanwhile, this study proposed an intuitionistic fuzzy integrated-based compromise solution (CS) and DEMATEL approach to rank the candidate by computing experts’ weights and determining criteria importance, respectively. In addition, the proposed approach is developed based on last aggregation approach to prevent the data loss during the preferences integration. Besides, a real case study of the bridge maintenance operation is proposed in Rasht city of Iran to represent the implementation procedure of the proposed IF-integrated approach. The results indicate that the pipeline project of water supply lines is considered as the best candidate among the four maintenance models candidate. Finally, the proposed method was compared with TOPSIS method to indicate the validity and the efficiency of the proposed method and emphasize its appropriateness.