فصلنامه چشم انداز مدیریت صنعتی
سال دوازدهم شماره 4 (پیاپی 48، زمستان 1401)

In this paper we try to simulate the life cycle of the electricity industry using the agent-based simulation method. For this purpose, 5 Agents were mentioned and they were simulated by Anylogic software .Then, four scenarios were investigated with experts' opinions. In the first scenario, it is assumed that the attractiveness of gas power and combined has been reduced and the attractiveness of the other two power has been added, the result of this scenario is the increase in hydroelectric power production, which is not cost effective due to the lack of water resources for the country. In the second scenario, with the arrival of a new technology, the household consumer decreased by 40%, and hydro and steam power with a capacity of 40% were working in the power generation cycle, the result of this scenario is the reduction of fuel consumption and also the shortage of electricity produced relative to the electricity consumption. In the third scenario, it is assumed that the consumption rate of all consumer factors has decreased, which results in the lack of investor factor investment. the fourth scenario assumes that all consumers' consumption is constant, as well as keeping the attractiveness developed by the government steady. As a result, the capacity of electricity generation has increased, but we are still facing power shortages.

Supplier segmentation is the basis for the decisions of supply chain managers with the aim of managing and developing suppliers. The purpose of this study is to provide a dynamic approach to designing strategies for supplier development and management. In this research, a two-step approach has been used because the characteristics of purchased items play an important role in the design of these strategies. In the first stage, purchased items are classified according to purchasing portfolio matrix and proper criteria.Then, in the second stage suppliers of each purchased items group are segmented based on two dimensions such as willingness and capabilities. Finally, for each segment of suppliers in each class of purchased items, we provide suitable strategies for supplier development and management. In this work, we used the Delphi method on order to select the best criteria. Then, the criteria weight are determined using Best-Worst method. In the following, the purchased items and suppliers are positioned using MADM method (PROMETHEE). We tested this method for suppliers in a steel company, and the results are explained.

Facility location along with taking account the competition is a critical component of strategic planning. The location affects the competitiveness and market share of new entrants, in long-term. Because of the complications of location problems, most of the location models are faced whit many different limitations. In this paper a competitive facility location model with three competitors which produce two commodities is developed. The problem is modeled in the form of a location-price game. A bi-level model is developed to investigate the location and price. In location-pricing models, the location decision should come before the pricing game. From the second level and the use of Nash equilibrium, equilibrium will be obtained. In this paper, probabilistic costumer behavior with the help of exponential function is modeled. A metaheuristic based on tabu search is proposed to search the optimal location-price solution of the model. Findings show that changing the equilibrium price affect the profitability of new entry firms.

In order to achieve competitive advantages in uncertain situations, one of the big challenges that organizations are faced is the risk reduction through creating resilient supply chains. Supply Chain resilience refers to the ability of supply chain to respond to disruptions. Disruption is an unpredictable event that has different internal and external sources such as natural disasters and operational risks. In this paper, a simulation model has been presented for analyzing the disruption in the natural stone industry supply chain in one of the stone factories in Iran using Arena simulation software. The simulation model has been run 100 times and the simulation time has been assumed to be one year. The validation of the model has been done by comparing the simulation results with actual information by calculating the mean absolute error. Moreover, some scenarios have been made for disruption management and resilience creation in the system. Then, the performance of each scenario was evaluated based on some criteria include fill rate, backorder cost and total cost. Finally, the redundancy scenario was chosen to be run in the real world. The results showed that a backup production line would be set up in the factory to make the system more resilient.

Due to the effect of random factors such as machine failure on the competitiveness of production organizations and the importance of production planning, failure-prone manufacturing systems have emerged to deal with uncertainty. In order to maintain a competitive market share and increase productivity and safety, industrial systems have resorted to a maintenance strategy to reduce failure rates and increased reliability. Increasing production capacity, providing more flexibility and ensuring customer satisfaction in terms of quantity, quality and timing have made the use of subcontracting with a revenue sharing approach a viable option in this study. In this research, a network of machines with relationship limitation and failure and accidental repair is considered. To prevent shortages, intermediate buffers and a final buffer are used. Another important parameter is determining the optimal frequency of preventive maintenance, which results in minimizing the cost of preventive and corrective maintenance and repairs. The goal is to determine the optimal production rate and preventive maintenance variables and subcontractor variables. Discrete-event-simulation is used for this purpose. After modeling in Arena, the best values of decision variables are obtained in the opt-quest platform, which leads to a 22.5% reduction in total system costs.

Nowadays, quality management is an important field for organizations, including the banking system, which faces fierce competition. Organizational Excellence Models serve as guides to help organizations improve their quality. The main aim of this study was to investigate the dynamic relationships between the approaches and criteria of the EFQM organizational excellence model and optimize the simulation of these relationships. To do this, we first identified the common approaches in the organizational excellence model and clustered them using the fuzzy clustering method. Next, we used the systems dynamics method of causal rings to discover the dynamic relationships between these approaches. Finally, using data from the banking system in Iran, we simulated cases and optimized the growth rate of organizational excellence in the sample over 20 years (2018-2019).

Due to the uncertainties in the construction projects and their differences with the service and manufacturing industries in terms of scope of the work, environmental factors, executive and scheduling challenges, contractors and clients always face with significant damages, regarding contractual disputes. In such circumstances, it is essential to empower contractors in making contractual claims and managing the claims. The aim of this study is to identify contractors’ challenges in the claiming process and the way for dealing with these challenges. In this regard, these challenges along with the most important shortcomings of claims are identified, analyzed and prioritized. Research method including literature review, analysis of 16 claims in 4 projects, interviewing with ten experts and finally applying a questionnaire method, by obtaining 60 experts opinions about 38 challenges and the key shortcomings of the claim’s statements have been done. According to the research findings, 40% of the challenges are related to contractors and their internal organizational processes, 29% of the challenges are related to governmental organization and their rules, 21% of the challenges are related to clients and finally 10% of the challenges are related to the consultants and their monitoring systems.

Given the vast, continuous and increasing changes in global markets and customer demand, the use of powerful and reliable tools to support decision makers is inevitable. For this purpose, in this research, we have tried to address the issue of production planning by considering the system dynamics and uncertainty in customer demand. The production system assumed in this model is a hybrid push-pull production system. By applying this approach, the proposed model is also adapted for a fully push or pull production system. Production planning is usually done in the medium term, and the decisions made at each stage of time will also affect future plans. Therefore, in the face of potential customer demand, the multi-stage stochastic programming method has been used in order to make decisions with a view to the entire time horizon. The purpose of the proposed model is to maximize profits through the optimal use of production capacity, appropriate pricing policies and material resource planning. Finally, the proposed model is examined through conventional numerical analyzes in the stochastic programming method.