Journal Of Industrial Engineering International
Volume:16 Issue: 4, Autumn 2020

In this paper, a data mining approach is proposed for duration prediction of the town trips (travel time) in New York City. In this regard, at first, two novel approaches, including a mathematical and a statistical approach, are proposed for grouping categorical variables with a huge number of levels. The proposed approaches work based on the cost matrix generated by repetitive post-hoc tests for different pairs. Then, a random forest model is constructed for the prediction of the type of trips, short or long. Finally, based on the trip type and each of the mathematical and statistical approaches, separate artificial neural networks (ANN) are developed to predict the duration time of the trips. According to the results, the mathematical approach performs better and provides more accurate results than the statistical approach. In addition, the proposed methods are compared with some other methods in the literature in which the results show that they perform better than all other methods. The RMSE of mathematical and statistical approaches is, respectively, 4.23 and 4.27 minutes for short trips, and the related value is 9.5 minutes for long trips. In addition, a modified version of the nearest neighborhood approach, entitled modified nearest neighborhood (MNN), is proposed for the prediction of the trip duration. This model resulted in accurate predictions where its RMSE is 4.45 minutes.

During the last three decades, the concept of integrated decision making in the supply chain becomes one of the essential aspects of supply chain management (SCM). This concept explores the interdependence between facility location, flow allocation between facilities, transportation system structure, and inventory control system. This study presents a new form of the location-routing problem of facilities under uncertainty in a supply chain network for deteriorating items through taking environmental considerations, cost, and procurement time and customer satisfaction into account, to simultaneously minimize total system costs, maximal delivery time and emissions across the entire network and maximize customer satisfaction. The research problem is formulated in a mixed-integer nonlinear multi-objective programming. In order to solve the model, the combination of the two Benders decomposition algorithm and Lagrange multiplier liberalization, as well as the combination of red deer algorithm and annealing simulation, was proposed. For validation, the results of the proposed algorithm in different size examples are compared with the results of the exact method solution by MATLAB software. The mean error of the proposed algorithm for the objective function is less than 4% compared to the exact method in solving the sample problems. Besides, the results of the algorithm performance are investigated based on standard indices. The computational results show the efficiency of the algorithm for a wide range of problems with different sizes. The location decisions are interdependent, and the process of determining the optimal values of these variables interact together, which can lead to an optimal system.

Sawmills are an important part of the forest supply chain, and as at any company, their production planning is highly complex. Planning in the remanufacturing area, in terms of its economic contribution to the sawmill and the supply chain, has not been studied in the scientific literature. The goal of this study was to develop and solve a mixed-integer linear programming model by employing an efficient allocation of cutting patterns on in-stock logs to maximize profits. To quantify the impact of an appropriate use of raw materials in the remanufacturing area in a sawmill, real and generated data were used. The model considers fixed and variable production costs, the availability of raw material, the capacity of the processes, the sale price of the products and the demand, for a process period of one month. The proposed compact mixed-integer linear programming model was solved using the commercial solver IBM ILGO CPLEX12.8. It was determined that the additional margin in USD earned in the remanufacturing area for the considered scenarios amounted to an average of 21.6%. The proposed method facilitates evaluating the economic contribution of remanufacturing while identifying bottlenecks and assessing proposed scenarios.

In recent years, many organizations have made attempts to identify, measure, and manage their intellectual capital (IC). The efficiency of IC largely depends on identifying its main components and their relationships. So far, however, no study has been conducted to clarify the interactions among those components or to develop a model for laying out a hierarchy of IC components. There is, indeed, an urgent need to analyze the behavior of IC components so that the corresponding policies may be successfully implemented. This paper aims to identify the relationships among the IC components with a focus on the banking industry. A literature review was used to identify the 16 most important IC components. The Interpretive Structural Modeling technique was practiced to determine the interrelationships among these components, based on the data gathered from the Export Development Bank of Iran. The interconnections between the components were clarified. Furthermore, MICMAC analysis and classifying them into four categories including autonomous, driver, dependent, and linkage components regarding their driving and dependence power is a new effort in the field of IC. A hierarchical structure was proposed through prioritizing, sequencing, and leveling of the components. The adoption of such an ISM-based model of IC components in the banking industry would provide insights for managers, decision makers and policy makers for a better understanding of these components and to focus on the major components while managing their IC in their organizations.

The aim of this research is to prepare a comprehensive pattern for sustainable development namely, sea transport which is one of the important parts of the transportation industry. The mention focused on improving communications and coordination among maritime organizations in this area. The research written based on a descriptive correlative research method. In the data gathering; we have used a Field – Librarian Method. First, the Delphi method has been used to examine the framework for sustainable development and its effective components in the mention industry. Required information has been gathered by survey tools such as observations, interviews and questionnaires. Also structural equation technique, path analysis and LISREL software are used to analyze the gathered information. The conclusion of this research is representing a suitable model for explaining the relationships among stakeholder demands, supply chain performance and sustainable development so that we can declare the demands and requests initiated of stakeholders has direct and indirect meaningful relationships with sustainable development. In the long term; relevant organizations will be able to respond effectively to the needs and requests of key stakeholders and also will implement professional human resources which to be one of the most influential elements in the conceptual model.

This paper aims to conduct a research on the labor-management negotiation in chicken evolutionary game models through catastrophe theory. The both players can compromise or not during the negotiation. The "no compromise" strategy for labor means threat to strike and for management is ignoring labors' demands. Since the model of this research is chicken game, if on player decides to dig in, the optimum decision for other is to compromise, however it is costly to be calling a chicken by the rivals. In the process of evolution, players reevaluate their options to update the payoffs in case of gradual and continuous changes which may happen in effective variables of strategy selection. The continuous changes could cause a catastrophic change in system’s state and its collapse by a strike or lockout. ESS analysis and determining catastrophe threshold in the chicken evolutionary game will be done with the aim of giving managerial insights that help the players to prevent making decisions that could cause unsuccessful negotiation.

In many processes, quality characteristic is identified by the regression relationship between one or more dependent variables and one or more independent variables called profile. In this paper, a control chart based on discriminant analysis (DA) is proposed to monitor simple linear profiles in Phase II. A chi-square control chart joined with DA chart is also used to improve detecting variance shifts. Performance of the proposed method is evaluated in terms of average run length using Monte-Carlo simulations. Performance of the proposed control chart is compared to the basic methods in simple linear profile monitoring. Results present the desirable performance of the proposed method. The real case in shoes leather industry is also investigated to show the effectiveness of the proposed method. results also confirm an acceptable performance of the real case, because the average run length of the proposed control chart is less than the average run length of the comparable method.

Inappropriate gate assignment has some consequences such as flight delays, inefficient usage of resources and customer’s dissatisfaction. Airports are service sectors and provide services to their customers. Passengers and airlines are two main customers of an airport. Current research presents a novel mathematical model for gate assignment problem to minimize customers’ dissatisfaction. In other words, passengers walking time as well as flight delays are minimized in as objective function. In this model, transit and non-transit passengers and also arrival and departure flights are considered. Moreover, operational safety constraints are inserted to avoid collision of large aircraft. The proposed model is solved by Benders decomposition approach. The model is applied in San Francisco International Airport for a 24-hour horizon. The result shows that walking time of non-transit passengers, walking time of transit passengers, delay in departure flights and delay in arrivals include 74.55, 23.32, 0.96 and 1.17 percent of the objective function, respectively.