جستجوی مقالات مرتبط با کلیدواژه "برنامه ریزی دوسطحی" در نشریات گروه "مدیریت"

The purpose of this research is to design and plan the production and distribution supply chain in an integrated manner.

By using the bi-level programing approach, it is possible to maintain the integrity of decision-making while managing the conflict between the goals and interests of the decision-makers. In the proposed model, supply chain design decisions are considered at the leader level and production and distribution planning decisions are jointly considered at the follower level. At the leader level, the three goals of minimizing the costs of the entire supply chain, maximizing reliability and minimizing adverse environmental effects, and at the follower level, minimizing production costs and minimizing distribution costs are pursued. Therefore, the proposed bi-level programing model is multi-objective and multi-follower. To calculate the credibility of SCOR12 model parameters, hierarchical data analysis technique and fault tree analysis were used. The carbon dioxide emission factor was used to measure the adverse environmental effects. Finally, meta-heuristic technique has been used to solve the proposed model.

The findings indicate that due to the high accuracy of the MOEA/D algorithm, the findings of this algorithm can be trusted for the supply chain problem.

This research is considered a new approach in terms of leveling the problem and choosing the problem of leader and follower. If the decisions related to the design and planning of the supply chain are made with the cooperation of the supply chain links and in an integrated manner, the probability of achieving more favorable results increases

In this study, a new two-level mathematical model is presented in order to design a logistics hub network in the supply chain of disasters and disasters. The leader level model uses the location of hubs and the determination of vehicles used. The objective function of this model is to minimize the cost of building hubs, transportation costs, and infrastructure costs to develop a logistics hub network. In the follow-up model, it determines the optimal routes for sending products to applicants with the aim of minimizing service delivery time. Given that solving two-tier models in the case where the follow-up model has an MIP structure, it is known as a difficult problem in research in operations and there is not always a definite solution for it, in this research an innovative algorithm based on complete counting. It is provided with high quality answers. According to the computational results, it can be observed that the developed algorithm is able to produce justified answers and of course it has an acceptable level in terms of the quality of the answers. Using the results of this research can be used as a management tool by crisis management organizations.

This paper aims to propose a knowledge sharing optimization model based on the game theory that optimizes both employer and employee(s) decisions simultaneously. This model is a bi-level programming model. The upper-level problem includes employer decision about the reward, and the lower-level problem contains employee(s) decisions about time and effort allocation to knowledge sharing activity. Mathematical formulation of the model designed based on previous literature and in the framework of Motivation-Opportunity-Ability. The proposed bi-level programming model provides a foundation to investigate more different parameters comparing with previous models introduced in the literature. This model considers opportunity and ability factors in addition to the motivation. Also, payoff functions in this model are non-linear and therefore is more consistent with real cases relative to previous linear models. Additionally, this model analyzes the effects of available time as a key factor. The bi-level model coded in GAMS using EMP syntax and solved for a set of randomly generated data using BARON algorithm. Results indicated that the increase of applicability of codified knowledge and impact coefficient of social comparison could improve organizational performance and also save the cost of reward system. Therefore, neglecting these two parameters in designing a reward system could lead to under optimized decision making. This research provides a basis to consider more parameters simultaneously and help to improve organizational decisions. However, based on the results, BARON algorithm is not efficient to solve big problems, so developing a more efficient algorithm is needed.

Providing a bi-level programming model to solve the simultaneous problem of supplier selection and order allocation in multi-echelon supply chain is sought. The model will be proposed so that at the leader level, the supplier selection problem with the objective of increasing system reliability and at the follower level, the order allocation problem with the objective of reducing cost of system are formulated and customers’ demand at the last echelon of the supply chain is considered as an uncertain parameter.

Modeling the supplier selection and order allocation problem is based on the bi-level programming model, so the robust optimization technique was used to deal with the problem of uncertainty and a bi-level genetic algorithm was used to obtain the optimal solutions.

The results obtained from solving a real problem in the steel industry under various scenarios indicated that there is an opposing relationship between reliability and cost objectives, and increasing the number of chain members can lead to an increase in system reliability and cost. On the other hand, as increased reliability can lead to higher system costs, reliability reduction, which is mainly due to lack of quality and deficiency issues, can also lead to an increase in customers' dissatisfaction and, ultimately, an increase in aggregate system costs. Moreover, the results obtained in uncertain conditions, in comparison with definite conditions, indicated an unfavorable situation.

In order to improve the reliability of supply chain, the average reliability of the echelons in supply chain, which are at the lowest (highest) level in comparison to other echelons, should increase (decrease) in order to avoid additional costs. Besides, the interactive approach in proposed methodology provides a suitable solution for maximizing the interests of leader and follower levels.

In this study, the design of a network for municipal solid waste management has been studied from the viewpoint of an organization (e.g. Municipality) which collects different types of waste from all over the city and pays waste generation points in exchange for waste. Determining purchase price for waste and forming outsourcing policies are matters to be decided upon. In case of outsourcing, auction will be held and the private company who their business is recycling and composting can participate by bidding, which results in the selection of an organization or non-outsourcing. The problem is modelled as a bi-level model, in the first level, Municipality decides as the leader on outsourcing, and if outsourcing is agreed upon, a company is selected. In the second level, bidders compete as followers in the auction for receiving more waste from the organization and offer prices.

In today's competitive world, maintaining competitive power of industries is the requirement of remaining in the competition. In the case of small industries, it also needs to think about strategies of making the industries more competitive in order to survive and have successful activity in competition. In many countries, one of the methods that have gained successful experience in increasing competitive power of SMEs is clustering these firms in a frame of “industrial clusters”. Considering the importance of industrial clusters’ role in regional economic development programs, providing the solutions of improving the performance of the clusters was always a concern for researchers and specialists of this field.
In this study, the process of product pricing as one of the most important factors which affects the profitability of industrial clusters is discussed by game theory approach. The proposed model focuses on the structural differences between supply chains and industrial clusters where the concept of Stackelberg game and bilevel programming model is used to determine the price of cluster’s products. In order to test the validity of the proposed model, the stone cluster data of Tehran are collected and using MATLAB software they are implemented in propose pricing game. Then, the results of the Stackelberg game between leader and cluster’s Stakeholders is been analysed.