Measuring performance of supply chain by relational network DEA: A game theory approach

An appropriate performance measurement system is an important requirement for the effective management of a supply chain. Because of the existence of the intermediate measures connecting the supply chain members, conventional data envelopment analysis (DEA) cannot be utilized directly to measure the performance of supply chain and its members. This paper evaluated the performance of supply chain under cooperative and non-cooperative games by utilizing relational network DEA. Relational network DEA model considers the interrelationship of the members within the supply chain, to measure the efficiency of the supply chain and those of the members at the same time. The non-cooperative game is based on the Stackelberg strategy solution concept. In non- cooperative game, it is considered that some parts in supply chain have more power in marketing competition (leaders) and the other parts of the supply chain repetition of supply chain are the followers. In the leader-follower structure (Stackelberg model), the leaders efficiency, first evaluated by using the relational network DEA in parallel situation, and then the followers efficiency is evaluated, using information related to the leader’s efficiency. In cooperative game it is assumed that all parts of supply chain cooperate to each other in order to achieve higher efficiency

Measuring performance of supply chain by relational network DEA: A game theory approach

An appropriate performance measurement system is an important requirement for the effective management of a supply chain. Because of the existence of the intermediate measures connecting the supply chain members, conventional data envelopment analysis (DEA) cannot be utilized directly to measure the performance of supply chain and its members. This paper evaluated the performance of supply chain under cooperative and non-cooperative games by utilizing relational network DEA. Relational network DEA model considers the interrelationship of the members within the supply chain, to measure the efficiency of the supply chain and those of the members at the same time. The non-cooperative game is based on the Stackelberg strategy solution concept. In non- cooperative game, it is considered that some parts in supply chain have more power in marketing competition (leaders) and the other parts of the supply chain repetition of supply chain are the followers. In the leader-follower structure (Stackelberg model), the leaders efficiency, first evaluated by using the relational network DEA in parallel situation, and then the followers efficiency is evaluated, using information related to the leader’s efficiency. In cooperative game it is assumed that all parts of supply chain cooperate to each other in order to achieve higher efficiency

A bi-level multi-objective data envelopment analysis model for estimating profit and operational efficiency of bank branches

Data Envelopment Analysis (DEA) is a powerful method for analyzing the performance of decision making units (DMUs). Traditionally, DEA is applied for estimating the performance of a set of DMUs through measuring a single perspective of efficiency. However, in recent years, due to increasing competition in various industries, modern enterprises focus on enhancing their performance by measuring efficiencies in different aspects, separately or simultaneously. This paper proposes a bi-level multi-objective DEA (BLMO DEA) model which is able to assess the performance of DMUs in two different hierarchical dimensions, simultaneously. In the proposed model, we define two level efficiency scores for each DMU. The aim is to maximize these two efficiencies, simultaneously, for each DMU. Since the objective functions at both levels are fractional, a fuzzy fractional goal programming (FGP) methodology is used to solve the proposed BLMO DEA model. The capability of the proposed model is illustrated by a numerical example. Finally, to practically validate the proposed model, a real case study from 45 bank’s branches is applied. The results show that the proposed model can provide a more comprehensive measure for efficiency of each bank’s branch based on simultaneous measuring of two different efficiencies, profit and operational efficiencies, and by considering the level of their importance

An Integrated Fuzzy Clustering Cooperative Game Data Envelopment Analysis Model with application in Hospital Efficiency

Hospitals are the main sub-section of health care systems and evaluation of hospitals is one of the most important issue for health policy makers. Data Envelopment Analysis (DEA) is a nonparametric method that has recently been used for measuring efficiency and productivity of Decision Making Units (DMUs) and commonly applied for comparison of hospitals. However, one of the important assumption in DEA is that DMUs must be homogenous. The crucial issue in hospital efficiency is that hospitals are providing different services and so may not be comparable. In this paper, we propose an integrated fuzzy clustering cooperative game DEA approach. In fact, due to the lack of homogeneity among DMUs, we first propose to use a fuzzy C-means technique to cluster the DMUs. Then we apply DEA combined with the game theory where each DMU is considered as a player, using Core and Shapley value approaches within each cluster. The procedure has successfully been applied for performances measurement of 288 hospitals in 31 provinces of Iran. Finally, since the classical DEA model is not capable to distinguish between efficient DMUs, efficient hospitals within each cluster, are ranked using combined DEA model and cooperative game approach. The results show that the Core and Shapley values are suitable for fully ranking of efficient hospitals in the healthcare systems

Global optimisation for a developed price discrimination model:A signomial geometric programming-based approach

This paper presents a price discrimination model for a manufacturer who acts in two different markets. In order to have a fair price discrimination model and compare monopoly and competitive markets, it is assumed that there is no competitor in the first market (monopoly market) and there is a strong competitor in the other market (competitive market). The manufacturer objective is to maximize the total benefit in both markets. The decision variables are selling price, lot size, marketing expenditure, customer service cost, flexibility and reliability of production process, set up costs and quality of products. The proposed model in this paper is a signomial geometric programming problem which is difficult to solve and find the globally optimal solution. So, this signomial model is converted to a posynomial geometric type and using an iterative method, the globally optimal solution is found. To illustrate the capability of the proposed model, a numerical example is solved and the sensitivity analysis is implemented under different conditions

Global optimisation for a developed price discrimination model:A signomial geometric programming-based approach

This paper presents a price discrimination model for a manufacturer who acts in two different markets. In order to have a fair price discrimination model and compare monopoly and competitive markets, it is assumed that there is no competitor in the first market (monopoly market) and there is a strong competitor in the other market (competitive market). The manufacturer objective is to maximize the total benefit in both markets. The decision variables are selling price, lot size, marketing expenditure, customer service cost, flexibility and reliability of production process, set up costs and quality of products. The proposed model in this paper is a signomial geometric programming problem which is difficult to solve and find the globally optimal solution. So, this signomial model is converted to a posynomial geometric type and using an iterative method, the globally optimal solution is found. To illustrate the capability of the proposed model, a numerical example is solved and the sensitivity analysis is implemented under different conditions

A fuzzy data envelopment analysis based on credibility theory for estimating road safety

Road accidents as a global challenge, imposing irreparable financial and human life losses in almost all countries, especially in developing countries, annually. According to world health organization (WHO), if this trend continues, road accidents will become the 7th cause of human death by 2030. Thus, road safety policy makers have been trying to use safety promotion and preventative actions. In this paper, the road safety performance of Iranian provinces is studied. To evaluate road safety efficiency scores, data envelopment analysis based on road safety (DEA-RS) method in two deterministic and non-deterministic situations is used. To consider the uncertainty in input and output data, this paper develops credibility DEA-RS (CreDEA-RS) model. In fact, the constraints of DEA-RS model are considered as credibility constraints and a counterpart credibility DEA-RS (CreDEA-RS) model is proposed for evaluating road safety of provinces of Iran. According to the results, provinces located in mountainous and forest areas such as Gilan had a much weaker performance than provinces in desert areas such as Yazd

Amalgam Surface Treatment by Different Output Powers of Er:YAG Laser:SEM Evaluation

Introduction: The purpose of this study was to evaluate amalgam surfaces treated by different output powers of erbium-doped yttrium aluminum garnet (Er:YAG) laser by scanning electron microscope (SEM).Methods: Twenty-one amalgam blocks (8 mm × 8 mm, 3 mm thickness) were prepared by condensing silver amalgam (into putty impression material. After keeping them for 24 hours in distilled water, they were divided into 7 groups as follow: G1: Er:YAG laser (1 W, 50 mJ), G2: Er:YAG laser (2 W, 100 mJ), G3: Er:YAG laser (3 W, 150 mJ), G4: Sandblast, G5: Sandblast + Er:YAG laser (1 W, 50 mJ), G6: Sandblast +Er:YAG laser (2 W, 100 mJ) and G7: Sandblast +Er:YAG laser (3 W, 150 mJ). Then after preparation of all samples, they were examined by SEM.Results: The SEM results of amalgam surfaces treated by different output powers of Er:YAG laser showed some pitting areas with non-homogenous irregularitiesConclusion: It seems that the application of sandblasting accompanied by Er:YAG laser irradiation can provide proper surface for bonding of orthodontic brackets

Finding the optimal combination of power plants alternatives: a multi response Taguchi-neural network using TOPSIS and fuzzy best-worst method

With increasing growth of electricity consumption in developed and developing countries, the necessity of constructing and developing of power plants is inevitable. There are two main resources for electricity generation includes fossil and renewable energies which have some different characteristics such as manufacturing technology, environmental issues, accessibility and etc. In developing plans, it is important to consider and address the policy makers’ indicators such as environmental, social, economic and technical criteria. In this paper, an integrated multi response Taguchi-neural network-fuzzy best-worst method (FBWM) -TOPSIS approach is applied to find an optimal level of five different power plants including: gas, steam, combined cycle, wind and hydroelectric. Taguchi method is used to design combinations and calculate some of the signal to noise (S/N) ratios. Then, neural network is applied to estimate the rest of S/N ratios. Finally, FBWM and TOPSIS methods are used for weighing sub-indicators and selecting the best combination, respectively. To illustrate the usefulness of the proposed approach, a case study on the development of power plants in Iran is considered and the results are discussed. According to the results, in general, small size power plants for fossil resources are preferable. In contrast, medium and larger size power plants for renewable resources are preferable