مجله مدیریت تولید و عملیات
سال دوازدهم شماره 2 (پیاپی 25، تابستان 1400)

This paper aims to develop a non-homogeneous NDEA model for measuring the efficiency of a mixed network with an open structure at each stage, interlayer connections, and uncertainties in inputs, outputs, and intermediate processes. 

To model the problem, a new model has been proposed first to determine the efficiency of each layer, based on the average weight of the layers. Then, the model has been developed to calculate the total efficiency. The Bertismas and Sim approach has been used to consider the uncertainty of inputs, outputs, and intermediate processes. Pistachio orchards in Yazd province have been selected as a case study, and relevant data of 10 cities in the Yazd province has been collected from the Agricultural Jihad Organization of Yazd province. 

The results indicated that with increasing the deviation in uncertain network data from 0.01 to 0.1, the average total efficiency decreased from 0.933 to 0.915. Such a reduction was also observed in the efficiency score of each of the DMUs. Reducing the average levels of efficiency and tightening the constraints on the proposed models reduced the number of units on the Performance boundary and eliminated the need to use super-efficient models to re-evaluate the efficiency. In other words, the computation of the total efficiency of decision-making units and sub-layers was enhanced. Research limitations/implications : The proposed approach was developed based on the model of Charans et al. (1978). As a limitation, the weighted sum of the outputs was less than or equal to the weighted sum of the inputs. The proposed model can be developed further to include other factors, such as undesirable outputs.

Findings can provide a more accurate understanding of the performance of the components of decision-making units to managers and decision-makers. This study highlights the usefulness of the proposed models as a decision tool in agricultural units. 

The developed models can be used in various social contexts. According to the case study, it is overemphasized that water resources management is significantly important for Yazd as a province located in an arid and desert region. Therefore, increasing the efficiency of orchards by identifying and improving inefficient processes, can lead to helpful-agricultural consequences in this province. 

While many studies have been conducted in the field of NDEA, this is the first study in the field of open non-homogeneous mixed networks considering uncertainty in all data, simultaneously.

Sharing capacity among the manufacturing companies, which are not competitors at the same level, can increase their profit and sustainability. This study aims to propose a model for identifying and determining the horizontal collaborative clusters in industrial holdings. 

 To achieve the mentioned clusters in the pharmaceutical industry, first, the affecting criteria were determined based on the literature review, and according to the opinions of managers, supervisors and pharmaceutical holding experts. Then, the related dimensions of each sub-criteria were specified and the common products of the companies were grouped into eight clusters. In this step, each drug was assigned to a cluster of which, the characteristic vector had the shortest distance from it. In the following steps, the obtained clusters were assigned to the companies. For this purpose, the similarity of clusters and companies were measured and each cluster was assigned to the most similar company. Finally, the quality of clustering was measured using cosine similarity, by calculating the distance between the company's products in pairs. The average value of such distances was assumed as the representative value of the product distance in the clusters. 

Pharmaceutical products were categorized into eight clusters, and each one was assigned to a company. Also, the components’ cosine distance inside each cluster was compared, before and after the clustering. The results indicated that the mean distance of products decreased after clustering. Since the similarity of the products in each cluster was increased, it seems that the clustering was sufficiently qualified. 

 One of the main limitations of this study was the lack of a consistent standard in the information provision of companies. Another limitation was the lack of transparent information provided by companies and the time required to collect data. Also, there was a lack of related studies on how to implement such a method. The lack of cooperation of some experts in completing the questionnaire brought other difficulties and led to a longer-lasting research time. As a future study opportunity, it is suggested to perform a feasibility study on the horizontal collaboration in industrial holdings according to different variables such as holding size (small, medium, large), type of industry (manufacturing and commercial), type of sector (private and public) and legal status (Individual ownership, partnership), market demand and market size. Such study results in determining the extent to which, horizontal cooperation can bring synergy in different situations. 

Horizontal collaboration is an effective tool for business management to improve the competitiveness of the organization. It also fills the gap between the company's existing resources and future requirements. It also increases the competitiveness of organizations by providing external resources to them through creating synergy, promoting learning, and rapid change. Social implications: Holdings create synergies by establishing cooperation between their subsidiaries. The result will be higher production quality and more cost-effectiveness, which will lead to customer satisfaction.  

There are a variety of ways for determining a business partner, including game theory and clustering. While in several studies, cooperation among several factories through game theory negotiations has led to relative efficiency, decisions have been made based on a short-term perspective. Therefore, such cooperation may be unstable. The desired time horizon is long-term in clustering. Hence, the designated partners can consistently continue their cooperation in the long run.

This study aims to propose a multi-objective model for determining reliable suppliers of one-shot systems. Design/methodology/approach: First, based on the evaluation indicators, the risk of each supplier is estimated. The subsets’ risks are also evaluated using the causal-effect matrix. Considering possible events for the one-shot case and analyzing a fault tree led the researchers to meet the best composition of equipment. 

The proposed model is capable of leading practitioners to allocate suppliers effectively when a one-shot case is considered. Research limitations/implications: The results of this study are referred to the current equipment of the focused one-shot system. Also, the results are limited to potential risks identified, evaluations related to comments, and the proposed model for the considered time interval. 

Based on the findings, applying the proposed approach can lead to an effective management tool for selecting suppliers with acceptable risk in one-shot systems.  

A one-shot device is defined as a unit that can be used only once, hence the device cannot be used for testing more times. Each subset used in one-shot systems, regardless of how it supplies, has a specific risk level. Depending on what any subset provides, it also affects the factors influencing the overall system failure. Therefore, selecting appropriate suppliers is significant to ensure correct function of a system. 

The proposed model can be used as a fast and reliable method for determining appropriate suppliers for one-shot systems, whose results can be relied upon with a suitable approximation in respect of the sensitivity analysis. To the best of the authors’ knowledge, nobody else have addressed the problem in such a way.

Project deviations are so significant that various methods have been proposed to measure them over the years. Earned Duration Management (EDM) is a method that measures project evaluation indexes only by considering the past trend of project execution compared to the baseline program. It ignores all the other factors, which cause much information to be lost to guide managers. Therefore, in this study, a process is proposed. During this process, it is possible to develop EDM indicators using key performance indicators of project quality in a fuzzy manner and based on the identified substantial risks. 

A list of risks was initially identified based on the PMBOK standard's category, and project managers selected the most important ones. In the next step, based on the most critical risks, two key indicators of project equipment and execution performance were defined. Such indicators were presented to managers again to determine their future impact on the project. By defining a triangular fuzzy number, the definite evaluations became fuzzy, since experts expressed the effect in linguistic variables. Finally, the indicators entered into the EDM, and the method was developed. 

In this study, Key Performance Indicators were used to increase EDM’s accuracy. First, the three risks of delay in receiving project resources, lack of timely allocation of financial resources, and disruption in materials preparation were identified as the main risks. Then, to study the status of the risks, two indicators were defined (PSI, PEI). These two indicators were estimated, up to 50% of the simulated project. Concerning the first indicator, the more the value, the more acceptable project performance was. Considering another indicator, the situation was contrariwise. Then, the future status of the indicators was examined by consulting managers and making the indicators in a fuzzy manner. The effect of the indicators was determined through the EDTC variable in the EDM. It should be noted that the final estimated time was used to measure the accuracy of the proposed method. The studied project was simulated using the prevailing situation in Matlab software. The end time of this simulated project was estimated at 1300 days. Then, the project was evaluated day by day till its 50% completion using EDM, and the end time of 1225 days was estimated. The same evaluation was performed for the proposed method, and the final time (1270, 1247, 1240) was determined. Because this time was closer to the simulated time, it was evident that the proposed method had the highest accuracy.

In this study, to prevent information disclosure, project simulation was used instead of the actual project to evaluate the indicators and advance the project. Therefore, although the accuracy was estimated in this paper, its more exact value might be requested in future research. Consequently, the proposed method can be applied in an actual project, and the accuracy of the model can be measured, consequently. 

The proposed process and method in this research can be used in the implementation and planning stages of any other project. The process should be localized because the risks vary from project to project. Besides, the critical risks of each project cannot be compared with the other projects. Therefore, after examining each project's risks and defining indicators related to the selected risks, the proposed method can be applied in all project-based organizations and on any project type.

Today, the construction and operation of projects are among the factors that affect the countries' growth and development. Deviations from the budgets allocated to the project are an integral part of project implementation and are not dependent upon a specific area or even a particular management and implementation method. Therefore, proper planning and control of projects are essential. This paper provides an effective model for senior project managers to complete projects on time. Successful implementation of projects leads to economic prosperity. Also, improving the quality and performance provides a calmer social environment for people and creates many environmental benefits.

In this study, the indicators of the EDM method were developed using the key performance indexes. Such indexes were associated with the quality of project performance execution and were estimated under uncertainty conditions; thereby, more information can be transferred to the project management. The defined performance indicators are measurable during the process, and their impact on the ongoing project is monitored. The innovations of this study are twofold: Applying the performance index developed the EDM method; and defining the quality performance index in fuzzy terms.

In this paper, the flexible manufacturing system lot-sizing with the co-production problem is modeled. It is also simplified using the relationships between variables. One of the common methods for solving such problems is the fix and optimize algorithm, which is generally used in a one-dimensional approach. Also, a two-dimensional fix and optimize algorithm is applied to solve the problem. This algorithm is compared with two common algorithms using simulated data series.

In this paper, Flexible Manufacturing System Lot-sizing with Co-production problem is modeled using mixed-integer programming. The production of products in this flexible system varies with the change of production mode, and a different mixture of products is produced for each production mode. Also, the planning interval includes T periods, and the demand for each product in each given period is constant. In each period, a fixed setup cost is added to the production and maintenance variable costs, if production occurs. The objective function of the model minimizes the sum of fixed setup costs and production and maintenance variable costs of inventory in each period and each production mode. Problem constraints include setup forcing constraints, inventory balance constraints, initial inventory constraints, co-production constraints, production mode constraints, non-negative variables constraints, and binary variable constraints. Among the methods proposed to solve this group of problems, the fix and optimize method is one of the most effective and general methods. The basic idea of ​​this approach is that due to the difficulty of solving the main problem with a longtime interval, a problem with a shorter time interval called the time window is solved instead. Except for the variables in the time window, other integer variables are considered continuous variables, so the resulting problem is easier to solve. In the following steps, the time window variables in the current step are assumed constant, and this repetition will continue until the end of the desired periods. Time windows can be considered with or without overlap. In this paper, two innovative one-dimensional fix and optimize algorithms based on time and production mode variables and a new two-dimensional algorithm based on time and production mode variables are applied to solve the model using simulated data at three levels of small, medium, and large scales. MATLAB 2016 software is used to code the algorithms of this study, and numerical calculations are performed by a personal computer with Intel®Core™i3-7100@3.90GHz processor and 8 GB RAM. 

The research results indicated the significant superiority of the proposed two-dimensional algorithm in terms of response time over the two one-dimensional algorithms. It is important to note that in terms of the quality of the answer in the studied problems, no significant difference was observed. 

In many real cases, due to the fact that the cost parameters in different production situations (e.g., the oil, gas, and petrochemical downstream industries) are close to each other and in practice, determining production conditions in accordance with other parameters such as demand is independent of production costs, the efficiency of the proposed algorithm will be more visible in this article. The most important limitation in this study was the lack of real data for a flexible production system with correlated products, which is why simulated data were used to validate the model and test the proposed algorithms.

In the future, researchers can use real-time case studies based on the proposed model and algorithms in this paper. They can also add other features to the model, such as limited production capacity and allowable shortages. Manufacturing plants that have features similar to this study can benefit from the findings to optimize production costs.

Applying the results of this research can increase the productivity of production units and the use of non-renewable energy resources.

In this paper, a mathematical model (MILP) was proposed for the Flexible Manufacturing System Lot-sizing with Co-production problem. In addition, an innovative two-dimensional fix and optimize algorithm was developed.

In the aviation industry, selecting the right new flight route and planning associated necessary capacities have a significant impact on airline revenue. If the selection is not done successfully, the company will face irreversible and costly effects in the long run. A new route is selected based on several criteria, most of which are contradictory. Choosing the right criteria and decision methodology leads to meeting the company's goals, which is significantly valuable. This study aims to select flight routes among the potential destinations for airlines.

To determine the final indicators from those extracted from the literature review, a survey questionnaire was developed based on the five points Likert scale (very low to very high) to collect the experts' viewpoints.  Being an airline executive with more than 20 years of experience and having at least a bachelor's degree were the selection criteria for the experts. After summarizing and averaging the viewpoints received, the criteria with less than the threshold of 60% of the total average score were removed (according to the Friedman test). Then, the final weight of each criterion was determined using the Fuzzy Hierarchical Analysis Process (FAHP). To verify the answers of the experts, the compatibility rate of the criteria and sub-criteria was calculated using Gogus and Butcher method. Then, using the COPRAS method, the priority of options, i.e., new flight routes were determined in the flights of Iran Air. 

The results indicated that among the four selected criteria, the economic criterion had the highest weight. Examining the weights obtained from the sub-criteria also indicated that in the economic criterion, the sub-criterion of "gross revenue expected by the company from established airline", in the marketing criterion, the sub-criterion of "tourism and trade flow rate", in the performance criterion, the sub-criterion " conformity of capacity of existing fleet with flight demands", in the geographical criterion, and the sub-criterion of "the effect of seasonal fluctuations on the route" were identified as the most significant sub-criteria. Also, the gross revenue criteria expected by the company and the number of airlines with the desired route were the most significant sub-criteria. Finally, among the five routes, the route from Tehran to Assaluyeh and the route from Ramsar to Mashhad were ranked as the first last routes.

One of the limitations of this study was the emphasis on domestic flight options due to the effects of sanctions, the problems faced by Iranian airlines, and the inability to provide world-class service to international passengers. As a result, the weight of the selected criteria on international flights may differ from the results obtained in this study. Also, the occurrence of the Covid-19 pandemic may affect the intention to travel by airlines, even in post-corona conditions, the effect of which has not been studied yet.

Selecting a flight path is one of the most practical concepts for airlines, which can be considered by appropriate criteria to make transportation criteria fit with the revenue generated. When the new route is selected according to the right criteria, both the number of trips and the airlines' revenue increase.

Creating new airlines will lead to the development of aviation, affecting the value chain of transportation directly and indirectly. According to recent estimates by the Air Transport Action Group, the impact of the whole economy (direct, indirect, induced, and related to tourism) on the global aviation industry is about 3.6% of the world’s GDP. The aviation industry has also created 65.5 million jobs worldwide of which, 10.2 million are direct jobs, and 55.3 million are indirectly related to the tourism industry.

Issues such as the specific conditions of the country related to sanctions and problems in the development of airlines (due to restrictions on aircraft imports), the monopoly of domestic airlines, differences in lifestyle, and cultural issues have made the determination of new airlines in Iran different from other countries. This issue makes it impossible to generalize its significant criteria to other parts of the world. Therefore, this study contributed to the identification and determination of the importance of air transportation criteria and the selection of new flight routes in the country.