نشریه پژوهش های نوین در تصمیم گیری
سال ششم شماره 1 (بهار 1400)

The service segment, directly and indirectly, has a significant share of GDP. Among these, consulting engineering services is one of the most important service providers in various industries, which due to dynamism, uncertainty, and increasing global competition, Its continuous development is an inevitable necessity to meet the needs of customers.Identifying the challenges and how to develop consulting engineering services with the use of soda cognitive map with an emphasis on finding the steps of the process of creating a new engineering service, determining the factors affecting the process, and the marketing of this service is the main purpose of this research. The statistical population of the research is experts in the field of project consulting engineers who were selected using a purposive sampling method and research data were collected through in-depth and semi-structured interviews. The findings identified eleven steps to create a new engineering service and five key factors influencing the process. The marketing approach of the new engineering service based on the STP strategy was also explained. Validation of the findings was performed based on selected criteria related to qualitative research, which results indicate an acceptable level of validity and reliability.

Effectiveness of the organization and its economic evaluation is one of the most effective factors for the success of managers in the progress and development of organizations. The banking industry is the most important sectors in any economic system. The banking system for economic financing must have an efficient and effective performance. In this paper, we proposed a new model for evaluating cost efficiency and effectiveness, with considering the interaction and relationship between the internal departments of the bank branches, which is able to determine how to make optimal use of available resources in each section. We analyze the features of the proposed model, also the effect of the relationship between the sections on cost effectiveness is determined. In this model, the relationship between the sections is examined in two modes, free and fixed communication; we have used the proposed model to determine the efficiency and cost-effectiveness of 26 branches of a commercial bank in Iran, in two state, constant return to scale (CRS) and variable return to scale (VRS) and comparison of the results of the two state is presented. The results show that a branch that is cost-effective in both section, it will not necessarily be cost-effective. In addition, this model can provide more accurate information to managers to make decisions by identifying ineffective factors in bank branches.

The purpose of solving the problem of vehicle routing is to find a suitable route taking into account the existing conditions in the transportation problem. In this case, considering the routing conditions with several depots along with imposing traffic restrictions on some vehicles on some routes, will create quite real and complex conditions. Furthermore, in some cases, it is necessary to deliver the customer demand by visiting several times. For this purpose, in this research, by simultaneous considering of multiple depots, split delivery and traffic restrictions, it has been tried to bring the conditions of the routing problem very close to real-world problems. In this paper, after presenting a mathematical model, the problem is solved in small-size instances using CPLEX solver. Then, due to NP-Hardness of considered problem, to solve it on a larger size instance, a variable neighborhood search algorithm is proposed. Finally, the simulated annealing algorithm is used to validate and evaluate the quality of the proposed algorithm. The computational results show that the proposed algorithm has good performance in terms of runtime and solution quality.

One of the strategic parts of the health system is the blood supply chain. Blood is known as a vital and key issue with a sharply increasing demand for which over an earthquake. Sufficient blood supply, particularly in emergencies, is a major challenge. Properly locating the blood donation centers plays a significant role in supply management. In the present paper, the problem of routing-locating of the blood products supply chain in the event of an earthquake crisis has been reviewed, considering the magnitude of the earthquake (Richter) (case study: Tehran city). The objectives of this paper include minimization of the costs and time of sending blood products, location of blood collection centers and temporary treatment centers, as well as routing the distribution phase. The Euclidean method and the shortest route algorithm are employed in this paper in order to specify the route of vehicles, while Arc Map and Arc GIS software are used for location. The results suggest that bases close to blood centers should be chosen for construction to reduce costs, and given the desirability, donors should be allocated to nearby bases in order to obtain more desirability, and temporary medical centers must be established in suitable areas to cover most of the injured victims. Furthermore, the results indicate that through determining safe routes, blood supply chain users will be able to make proper decisions.

Time, cost and quality are important goals of any project. Todays, the demand of project stakeholders to reduce total project costs has increased simultaneously time reduction and augment in quality of the project. This leads researchers to develop models that add quality factor to previous models of cost-time balance. In this paper, a time-cost-quality trade -off model with three objective functions includes minimizing project termination, minimizing total project cost and maximizing total quality of activities in a multi-modal PERT network was investigated. After presenting the appropriate mathematical model, a decision was made on the basis of a test plan of possible levels for each variable. Then, using the simulation process, random values of decision variables and response variables were implemented at each time, and we developed a neural network model using artificial neural networks. To solve this model, since the problem is in the NP-hard category, two multi-objective meta-heuristic algorithms NSGA-II and MOPSO were used. To determine the performance of the proposed model, the problem was tested on a small, medium and large-scale PERT network. The parameters of these two meta-heuristic algorithms were adjusted by Taguchi method and the results were based on the parameters set showed that the NSGA-II algorithm performs better than the MOPSO algorithm.

Environmental pollution is a serious threats to global warming and human health, and most industries, especially the steel industry, are sources of environmental pollution, so reducing and controlling pollution from this industry has become particularly important in recent studies. Therefore, the purpose of this study is to identify the environmental criteria of Yazd steel industry in order to provide a causal model and analyze the relationships between them. In this study, first, by studying the thematic literature using the content analysis approach, the criteria that had a very low number of repetitions were removed from the list and interviewed with steel industry experts to localize and identify more practical criteria and 36 final environmental criteria were selected. A questionnaire was used to collect data and its validity and reliability were confirmed. Finally, a fuzzy cognitive mapping approach has been used to investigate the intensity of relationships and how the criteria affect and model design, and each of the criteria has been analyzed within the framework of this model. Accordingly, the criteria of green marketing, environmental design and environmental performance have the most influentiality, respectively, and the criteria of green marketing, green warehouse and building and environmental performance have the most impressionability in this industry, respectively.

In today's highly competitive world, closed-loop supply chains (CLSC) have become a major challenge for product recycling. The recycling system has a special place in the supply chain due to the coverage of laws and the reduction of environmental pollution, increasing economic power by creating new jobs and the ability to recover the value of returned products. The purpose of this study is to design fuzzy- goal model for optimizing the cost and distance of vehicles in the four echelon closed-loop supply chain. The closed-loop logistics model could not be easily solved with the base gradient methods due to its NP-Hard problem group, so the ant algorithm was used for optimization. Finally, after implementing the fuzzy goal model of the research, it was found that the goal of minimizing the cost in the model has a higher membership amount than the distance goal, and managers should pay special attention to this goal.

In Iran, Although the PET recycling industry is new, due to the appropriate economic return, many individuals and companies have turned to this industry. Creating a proper structure in the distribution and collection network of these products can provide a good base to replace its consumption with more environmentally friendly products. This paper aims to present a mixed integer linear programming (MILP) model for designing a supply chain network in which customer demand is dependent on the price offered by distribution centers. The proposed model addresses two main global trends in this industry: 1- Economizing the collection and recycling of bottles, 2- Price sensitivity analysis on demand for PET bottles. In addition, we applied a recently developed optimization algorithm (TLBO) to this problem with significant modifications. Since the standard version of TLBO is introduced for continuous representation methods and the representation method used in this paper (priority-based encoding) is and discrete method, modifications have been made to convert this method to a continuous one. Finally, the performance of this algorithm is assessed in terms of the quality of answers and the convergence speed and compared with two other meta-heuristic algorithms.

Missing data is a chronic disease in applications of data envelopment analysis. Very often, ‎important input or output variables are not completely specified and/or the decision-‎making units do not report all the required statistics. Therefore, the missing values in the ‎inputs and outputs cannot be studied using the original data envelopment analysis models. ‎This paper introduces methods for finding missing data when the existing data is certain. ‎In this article, after explaining the essential concepts of missing values, we describe some ‎methods of missing value imputation that reduce the complexity of data analysis. There ‎are several methods for imputing missing data, including various methods of simple ‎imputation and multiple imputation. This paper is the first systematic attempt to utilize data ‎containing missing values using statistical approaches in the DEA. In particular, we ‎examine what happens if we keep empty entries in the data set and assign a certain ‎numeric value to them. To show how the proposed methods work, they will be used to ‎evaluate a set of secondary public schools in Greece in some of which there are missing ‎input or output values.‎