Industrial Management Journal
Year:2021 | Volume:13 | Issue:2|Papers Count:8

Objective: A significant challenge in the university meal booking is the high No-Show rate that leads to considerable food waste in consequence of facing low price of nutrition system and government subsidizing. This study aims to prevent food waste in university dining halls via predicting actual demand. Methods: To model and solve the problem, an Artificial Neural Network has been used that was performed by weighting the error function with Generalized Pattern Search (GPS). Date, the day of the week, the price level of Food, total number of reservations, total number of reservations by undergraduate students, Masters' students, PhD students and dormitory students and the parallel food have been considered as inputs of the model. The output is the actual demands based on Show's number. Results: The seven-year data of the meal booking system of a large university in Iran has been examined. This data demonstrated that the food waste rate is close to 10% of the total food reservations. An artificial neural network including weighted error function under GPS optimization was obtained to predict actual demand. Finally, the results of training indicated over 80% waste reduction in surplus daily food production. Conclusion: The proposed model has the potential to provide an estimation of actual demand. Although adding indicators that influence demand estimation, the proposed model is able to change the actual demand prediction at various levels of risk expected by the university. To avoid food waste and prevent the loss of government subsidies, this precautionary approach can control overproduction.

Objective: Hospitals are one of the most important elements of the health sector, which is the most important and costly part of them are operating rooms. Therefore, locating and allocating resources appropriately and appropriate scheduling for the operating room, can greatly solve the health problems of the community. In this article, an integrated model for locating-allocating and scheduling the operating rooms to build facilities at the appropriate places, allocating patients to facilities and operating rooms and scheduling operating rooms with the goals of reducing costs and reducing the overtime of the operating rooms, is presented. Also, surgeons have the maximum working time per day, and then their performance is faced with an error. Methods: Given the NP-hard of the model and the inability of accurate methods for solving large-scale problems, a metaheuristic method based on the genetic algorithm has been developed for the problem and its efficiency has been studied in a wide range of samples examples. Results: Computational results showed that the proposed algorithms can effectively help to generate reasonable responses. Conclusion: The results of the problem indicate the importance of locating and integrating scheduling of facilities in reducing the waiting time of patients and their distance from facilities. The proposed algorithm is also capable of solving large-scale problems at an efficient response.

Objective: Over the past decade, there have always been new paradigms in supply chain design. The green supply chain is a new concept that helps organizations deal with unexpected disruptions and minimize environmental impacts. The main purpose of this study is to present a multi-objective optimization model for a green-resilient supply chain network in cement industries. Dashtestan cement industries have been selected for validation and implementation of the model. Methods: After reviewing the theoretical foundations and experimental background, the network was designed. Then, an appropriate mathematical model was developed and validated by a case study. In this study, scenarios were defined in two modes of production surplus and non-production surplus. Data analysis in each scenario was performed with MATLAB software. The CPLEX solver was also used to solve the model. Results: The results showed that Dashtestan Cement Company's production surplus has no effect on supply chain resilience. Also, it can be concluded that if there is a production surplus, the cost of carbon dioxide emissions is less than the one in the absence of surplus production. Conclusion: The company's production level has little effect on the cost of carbon dioxide emissions and the amount of that in the designed network is mostly due to the carbon emission rate in the production nodes and arcs. Therefore, the reduction of carbon footprint in these parts of the network should be considered.

Objective: This research pursues two main objectives: 1) designing an integrated system for evaluating sustainable performance with an emphasis on the main executive processes of the cement supply chain, and 2) identifying the position and role of the criteria of this system in interaction with each other. Methods: Achieving these goals in Sepahan Cement Company (SCC) is pursued in two phases. First, the supply chain operations reference (SCOR) model is used to design an integrated framework for evaluating the sustainable performance of the cement supply chain (CSC). Second, interpretive-structural modeling (ISM) and MICMAC analysis are used to analyze the position and role of sustainable performance criteria in CSC main processes. Results: In total, 16 environmental criteria, 10 economic criteria, and 4 social criteria were identified. The contribution of the executive processes of sourcing, manufacturing, delivery, and return of the cement supply chain from these criteria were 11, 15, 7, and 6 criteria, respectively. In each process, key and effective criteria that played a fundamental role in promoting process sustainability were identified. Conclusion: Not all SCC processes play the same role in improving various aspects of sustainability (society, environment, economy). Identifying the key and effective metrics of each process provides managers and policymakers with an appropriate perspective on the preparation of sustainability improvement projects. Despite the presence of economic criteria in all four executive processes of the cement supply chain, the effectiveness of these criteria is not the same in all processes. Therefore, the preferences of decisionmakers can be different regarding the prioritization of projects to improve the sustainability of SCC.

Objective: Finding a subset of features is an issue that has been widely used in a variety of fields such as machine learning and statistical pattern recognition. Since increasing the number of features increases the computational cost of a system, it seems necessary to develop and implement systems with minimum features and acceptable efficiency. Methods: Considering objective, it's developmental research and in terms of two Meta-heuristic algorithms, namely genetic algorithm (GA) and multi-objective non-dominated sorting genetic algorithm (NSGA II). The multi-objective method compared to the single-objective method has reduced the number of features to 50% in all instances; it doesn't make much difference in classification accuracy. The proposed method is applied on six datasets of credit data, and the results were analyzed using two common classifiers namely, support vector machine (SVM) and K-nearest neighbors (KNN). Comparing two classifiers applied on datasets, K-nearest neighbors (KNN) compared to the support vector machine (SVM) has shown relatively better performance in increasing the classification accuracy and reducing the number of attributes. Results: Genetic algorithm and multi objective non-dominated sorting genetic algorithm have a good performance in increasing the accuracy of classification and reducing the number of attributes in feature selection problem of multi-class data. The results also indicate an increase in classification accuracy, simultaneously with a significant decrease in the number of features in both KNN and SVM methods. Conclusion: According to the results, the proposed approach has a high efficiency in features selection problem.

Objective: One of the effective factors in calculating the Malmquist productivity index (MPI) is to calculate cost efficiency changes. In some cases, especially when the issue of saving and observance of the consumption pattern is considered, prices are usually considered stepwise, so this research introduces a method for calculating cost Malmquist productivity index (CMPI) when the prices are stepwise and the cost function is a linear piece. Methods: In this paper, due to the presence of stepwise prices and piecewise linear costs, the stepwise linear cost efficiency model, as well as the (CMPI), were used as the baseline models to develop the calculating method of cost Malmquist index as the prices are stepwise. Results: By applying the proposed method to calculate the index of 14 confectionaries in the city of Islam Abad Gharb during the years of 2019 and 2020, it was found that four confectionaries had an increase in productivity and ten confectionaries had a drop in productivity; and in total the average efficiency of 2020 declined compared to 2019. Also, the main factor in the loss of productivity in units was the loss of their efficiency in 2020 compared to 2019. Conclusion: According to the findings of the paper, the models presented in the proposed method have increased the capability of classical models to calculate (MPI) in such a way that if the costs are piecewise linear, the more acceptable and real results can be achieved with the help of proposed models than the classical models.

Objective: Nowadays, the essence of knowledge-based companies is based on creativity and innovation and they are noticed for economic growth based on knowledge and technology, therefore, the affecting factors on the better performance and innovation of these companies are significant. The purpose of this study is to investigate the impact of networking capabilities of the science and technology park on the performance of companies that are mediated by innovation. Methods: This study is practical in terms of purpose and descriptive and surveys in terms of the data collection method. The questionnaires that are based on the standard questionnaire are used to collect data. The statistical population of the study are managers and employees of these companies that according to the rule of using structural equation modeling (SEM), 379 people are considered as the sample and filled out the questionnaire. For both the direct relations model and moderation model, data analysis was performed with the use of structural equation modeling. Results: The results showed, networking capability has a positive and significant effect on the innovation of the located companies in the park and subsequently the innovation of the located companies on their performance. The mediating role of innovation in the relationship between networking and performance was confirmed but the direct effect of networking on the performance of companies was not. Conclusion: The presented conceptual model in this study helps to develop this type of model in order to support the performance of located companies in the science and technology parks.

Objective: Uncertainty is inevitable in the real world; nonetheless, fuzzy logic is regarded as one of the approaches employed in modeling such uncertainty. Therefore, a new field of mathematical programming has been proposed that is called Fuzzy Mathematical programming. Following Bellman and Zadeh, the pioneers of the Fuzzy School of Mathematics, other researchers have developed various solutions to solve fuzzy problems considering various components of mathematical models in a fuzzy condition. The present study aims to develop a novel approach to resolve investment problems using fully fuzzy mathematical model. Methods: In general, defining the degree of fuzzy numbers, which is assumed to be fixed, should be utilized to solve the full fuzzy problem. Since the given problem is fuzzy, it is better to define a fuzzy degree to solve the problem. Thus, considering that all the components are better to be seen as fuzzy components, a fully fuzzy possibilisticflexible composite model with a degree of fuzzy definition is developed in this study. Results: Finally, the proposed model used to resolve an investment problem and the results were compared to the findings of previous models. Then, the results point out a significant improvement (about 250% in intial investment) in the proposed model, which is much better than previous models. Conclusion: In this study, fuzzy extent value derived from Jimenez's approach has been used to solve fully fuzzy problems. Therefore, it has provided the possibility of solving problems with multiple fuzzy objective functions and fuzzy constraints.