The Journal of Grey System

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1. The Greyness and Applications of Grey Set

Xican Li, Li Li

The Journal of Grey System 2024, 36 (6): 42-53.

摘要（302）

In order to quantitatively describe the grey properties of grey set, based on the possibility function of grey set, this paper discusses the expression method of the greyness of grey set and its applications. Firstly, the axiomatic definition and a method of calculating the greyness of grey set are given, and its rationality is analyzed through examples. Then, according to the principle of unity of opposites, the concept of whiteness of grey set is given, and the applications of greyness of grey set are analyzed. Finally, some examples are given to verify the validity of greyness of grey set and its application model. The results show that the axiomatic definition of greyness of grey set not only conforms to the grey immortal axiom, but also can quantitatively describes the dynamic evolution state of grey hazy set (grey set). The application examples show that the grey relational degree model and the grey decision model based on the greyness of grey set are feasible and effective. The research results not only enrich the theory of grey mathematics and grey system, but also provide a new method for grey relational analysis and grey decision.

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2. Entropy-weighted TOPSIS Multi-attribute Decision-making Model and Its Applications Based on Generalized Greyness

Li Zhang, Xican Li

The Journal of Grey System 2024, 36 (5): 15-26.

摘要（300）

In order to solve the decision-making problem that the attributive values are internal grey numbers and the attributive weights are unknown, this paper try to construct an entropy-weighted TOPSIS model based on the generalized greyness of interval grey number from the perspectives of proximity and equilibrium. Firstly, the properties of greyness distance are analyzed and the simplified formula for computing greyness distance is given. Then, a method to determine entropy weight based on greyness distance is given, and an entropy weighted TOPSIS decision-making model is established. Finally, the constructed model is applied to selecting brackish water irrigation pattern of winter wheat in North China Plain, China, so to verify its feasibility and effectiveness. The results show that the model proposed in this paper not only fully utilizes the measurement information of interval grey numbers, but also overcomes the influence of subjective factors on weights, and provide a new method for decision-making of unknown attributive weights and attributive value with interval grey number, and the interval grey numbers coexist with the real numbers. The application examples show that the model proposed in this paper is feasible and valid.

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3. Data-driven Dynamic Grey-Verhulst SEIRD Model for Public Health Emergencies Forecasting

Shuhua Zhang, Ming Liu, Bingjun Li

The Journal of Grey System 2025, 37 (1): 33-46.

摘要（283）

Determining parameters in infectious disease dynamics models is crucial for simulating and predicting the development trends of public health emergencies. Utilizing real-time epidemic data and grey systems theory, our innovative approach bridges the Dynamic Grey Verhulst model and the SEIRD model, which respectively have advantages in short-term and long-term forecasting. The new model features a dynamically adjusting decision cycle to accommodate evolving epidemic data. We constructed a dynamic grey Verhulst model using the principle of metabolism, enabling it to dynamically update and iterate important parameters of infectious disease models. This results in accurate simulation and prediction of epidemic dynamics. Taking the SARS-CoV-2 Omicron outbreak in Shanghai, China, in the spring of 2022 as an example, the proposed Dynamic Grey-Verhulst SEIRD model (DGVM-SEIRD) provides a data-driven, high-sensitivity and high-precision method for predicting public health emergencies. Sensitivity tests also confirm the superiority of our model. Furthermore, validation with H1N1 influenza data from Beijing, the COVID-19 outbreak in Wuhan and SARSCoV-2 emergencies in the UK reinforces our model’s accuracy. This methodology provides a highly flexible and responsive analytical tool for public health emergency management, offering scientific support for formulating more effective epidemic prevention and control strategies and emergency responses.

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4. Forecasting the Two-Stage Regional Population Ageing Structure by Employing Grey Compositional Model

Hui Li, Naiming Xie, Rafał Mierzwiak

The Journal of Grey System 2025, 37 (1): 1-15.

摘要（255）

Population ageing is a significant and global concern, particularly pronounced in China, where rapid ageing growth has been observed. This growth is uneven across regions, presenting urgent challenges for local governments. Accurate forecast of regional ageing structure is vital for developing and adjusting population, social, and economic policies. To address this, based on the compositional data, population ageing is firstly delineated into two stages: the structure of the elderly and that of the disabled elderly, and a data collection and pre-processing framework based on this division is constructed. Then, a novel non-linear dynamic grey Markov compositional model is developed to tackle this two-stage issue. Finally, using this model, the ageing structure is predicted and studied in Jiangsu Province, China, as an illustrative case. Experimental results show that the ageing structure will be further “aged” and “disabled”, and moderate disability is the core component of the rise in the disabled elderly. These forecasts align with current trends in ageing and provide a quantitative basis for governmental policy-making and adjustments.

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5. Research on China's GDP Growth Forecast Based on Grey Machine Learning Model

Tianxiang Yao, Xichun Liu

The Journal of Grey System 2024, 36 (4): 1-13.

摘要（245）

Based on Keynesian macroeconomic theory, this paper introduces economic indicators with Chinese characteristics, and constructs a multivariate grey machine learning forecasting model (IGM (1, N, X1 (0) )-IPSO-LSTM) to predict China's GDP growth. Firstly, IGM (1, N) model is constructed by changing the background value construction method of GM (1, N) model and introducing grey action constant A which reflects the change from the grey differential equation to the difference equation. Secondly, due to the low frequency and small amount of GDP data, constructing a two-layer LSTM model to increase the model complexity, so that the data can be fully trained. In addition, this paper uses nonlinear descending function instead of w to construct Improved Particle Swarm Optimization algorithm (IPSO), and adds Genetic Algorithm (GA) to IPSO to reduce the risk of particles falling into the local optimal solution. Finally, using IPSO to find the optimal parameters of LSTM model to predict China's GDP growth. By comparing the prediction accuracy of IGM (1, N, X1 (0) )-IPSO-LSTM model with other benchmark models, the prediction result of IGM (1, N, X1 (0) )-IPSO-LSTM model is the best. It is predicted that China's GDP growth rate in 2024 is 5.18% and in 2025 is 5.12%. By analyzing the trend development of China's economic, it is found that the forecast results are consistent with the expected trend of macro economy, which increases the credibility of the forecast results.

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6. Comparative Analysis of Grey Forecasting Models for Population Aging Prediction: A Case Study of Egypt's Demographic Evolution

Islam Mahmoud Sharafeldin, Naiming Xie

The Journal of Grey System 2025, 37 (1): 108-117.

摘要（230）

Population aging in developing nations presents complex demographic challenges that conventional forecasting approaches often struggle to address effectively, particularly when confronted with endogenous volatility in demographic structures and limited data availability. This study introduces an enhanced hybrid grey forecasting framework to predict population aging patterns in Egypt, incorporating advanced grey models to improve prediction accuracy and capture regional demographic variations. Using comprehensive demographic data from 2011-2023, we evaluate multiple grey forecasting models to identify optimal prediction methodologies for different population segments. Our findings reveal that the Grey Optimization Model with Interval Analysis (GOM_IA (1,1)) demonstrates superior predictive performance, achieving the lowest Mean Absolute Percentage Error for urban populations, rural and aged populations during the testing period. While, Unbiased GOM (1,1) model give the best performance for the total population prediction over the other grey models. The model projects significant regional variations in aging patterns, with urban areas experiencing accelerated aging rates compared to rural regions. This study makes several key contributions by it establishing a robust methodological framework for demographic forecasting in developing nations with limited data availability. As well as providing quantitative evidence of regional disparities in aging patterns across Egypt. Finally, offering a data-driven insights for policy formulation in healthcare infrastructure development and social service delivery. The findings have significant implications for resource allocation and policy planning in Egypt and other developing nations experiencing similar demographic transitions. Furthermore, our research demonstrated the effectiveness of grey forecasting models in capturing complex demographic patterns and supports evidence-based decision-making in addressing the challenges of population aging.

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7. Grey Information Relational Estimation Model of Soil Organic Matter Content Based on Hyperspectral data

Hong Che, Xican Li, Guozhi Xu

The Journal of Grey System 2024, 36 (4): 56-68.

摘要（225）

In order to overcome the uncertainty in hyperspectral estimation of soil organic matter content, this paper aim to establish a grey information relational estimation model of soil organic matter content based on hyperspectral data and grey information theory. Based on 76 samples in Zhangqiu District of Jinan City, Shandong province of China, the spectral data are first transformed by the nine methods such as square root, first order differentiation of the logarithm reciprocal, and so on, the correlation coefficient is calculated, and the estimation factors are selected by using the principle of great maximum correlation. Then, according to the principle of increasing information and taking maximum method, the spectral estimation factors of each sample are sorted from small to large, and the grey information sequence is formed, and the grey relational estimation model of soil organic matter content is constructed based on the information chain. Finally, the estimation results based on different information chains are fused twice, and compared with the commonly used estimation methods. The results of the method in this paper show that the average relative error of the 12 test samples is 5.576%, and the determination coefficient R2 is 0.934, and the estimation accuracy is higher than that of commonly used methods such as multiple linear regression, BP neural network and support vector machine. The results show that the grey information relational estimation model using hyperspectral data proposed in this paper is feasible and effective, and it provides a new way for hyperspectral estimation of soil organic matter and other soil properties.

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8. A Novel Time-varying Non-homogeneous Discrete Grey Model and Its Application in Forecasting Solar Energy Generation in Total North America

Lin Xia, Yuhong Wang, Yuxuan Han, Ke Zhou, Youyang Ren, Yiyang Fu

The Journal of Grey System 2025, 37 (1): 96-107.

摘要（223）

Accurate forecasting of solar energy generation in total North America is crucial for effective energy planning and environmental protection. However, challenges arise from the limited and complex nature of the data. This paper introduces a novel Time-Varying Non-Homogeneous Discrete Grey Model (TVNDGM(1,1)) to address these challenges. The model introduces an anti-forgetting accumulated generating operator as the weight accumulation function to effectively prioritize new information. Additionally, it extends the homogeneous discrete grey model into a non-homogeneous format, enhancing model adaptability to various samples. Applying the Whale Optimization Algorithm in selecting non-structural parameters further improves accuracy. Case study results demonstrate that the model achieves fitting and test errors of 2.28% and 1.65%, respectively, outperforming seven other methods, thus indicating superior predictive accuracy and stability. Forecasts suggest that from 2024 to 2030, solar energy generation in total North America will continue to rise, with an average annual growth rate of 20.31%. This study enriches the theory of new information prioritization within grey forecasting methods and provides technological support for global energy planning and development.

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9. Research on Grey Prediction of Regional Dual Energy Consumption Under Carbon Emission Constraints

Yuhan Xie, Chuanmin Mi

The Journal of Grey System 2025, 37 (1): 79-95.

摘要（217）

To enhance the modeling capability of the grey prediction model in the spatiotemporal domain, the paper proposes a novel spatiotemporal grey prediction model integrated with heterogeneous adjacency accumulation. Initially, an improved economic geographic gravity matrix is employed to characterize the spatial flow patterns of regional energy consumption, vividly illustrating the spatial interplay between non-adjacent provinces. Subsequently, a heterogeneous adjacent accumulation operator is incorporated to mirror regional discrepancies in energy consumption and bolster the robustness of the spatiotemporal prediction model. Ultimately, the novel prediction model is utilized to forecast the evolution of regional dual energy consumption within the constraints of carbon emissions. The findings of this research reveal the following: (1) By 2030, the total energy demand is projected to surge to 6.839 billion tons of standard coal, surpassing the predefined threshold of 6 billion tons. The prompt implementation of energy-saving strategies is paramount to expedite the attainment of carbon peaking. (2) Energy consumption intensity exhibits notable regional variability, with a spatially positive correlation in energy consumption intensity among regions. By 2030, it is anticipated that only 12 provinces, including Beijing, Guangdong, Shanghai, and Jiangsu, will attain the energy efficiency benchmarks of advanced developed countries.

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10. Equipment Maintenance Reliability Based On Grey Relational Decision Optimization Model

Qiang Li, Shupin Chen, Shumiao Fang, Ailing Yan, Wenjie Dong

The Journal of Grey System 2025, 37 (1): 133-144.

摘要（211）

Aiming at the selection of maintenance strategy for equipment reliability, This article first proposed a evaluation index system for equipment maintenance reliability from three perspectives: equipment operation guarantee, equipment maintenance, and equipment daily management and gives the modeling steps and flow chart of the grey correlation decision model, Delphi method and analytic hierarchy process are used to combine qualitative and quantitative analysis methods to determine and optimize the weight of qualitative indicators. Then, combined with the actual data of coating equipment operation and maintenance in a semiconductor panel manufacturing industry, a grey correlation decision optimization model is constructed to calculate the effect vector, the ideal optimal effect vector and the grey comprehensive correlation degree of the decision scheme of each index. Finally, through the grey correlation analysis, the optimal strategy selection of Coating equipment maintenance reliability is realized. The research in this paper has practical guiding significance for coating equipment maintenance decision-making, improving coating equipment maintenance reliability and reducing equipment maintenance cost.

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11. A Novel Power-sum Time-varying Grey Prediction Model and Its Applications

Kai Cai, Lianyi Liu, Sifeng Liu

The Journal of Grey System 2025, 37 (1): 64-78.

摘要（203）

The purpose of this paper is to propose an improved power-sum accumulation time-varying grey model (PATGM) to enhance the ability to mine the heterogeneity of sparse data. Firstly, a novel power-sum accumulation grey generating operator is introduced to smooth the observed values according to data fluctuations, mitigating the model's ill-conditioned property. Secondly, a time-varying function is introduced as a parameter structure to the traditional model, providing the model with flexibility in complex systems modeling. Finally, based on the Dingo Optimization Algorithm, a hyperparameter calibration strategy for PATGM is provided. The power-sum accumulation grey generating operator can amplify or minimize the nonlinear characteristics of the observations, thus significantly improving the adaptivity of the grey modeling approach to fluctuating sequences. Meanwhile, the elastic-net regression method is employed to obtain a more reasonable and stable parameter structure. The hyperparameters are calculated using the Dingo optimization algorithm, which effectively controls the noise resistance and nonlinearity in the prediction system. PATGM solves the data smoothing processing and model structure selection problems of the traditional grey model. This new model is suitable for processing data prediction tasks with complex characteristics, especially provides an effective prediction method for complex engineering and system modeling.

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12. Research on Image Recognition of Wood Defects Using TGARG Based on Edge Detection and Characteristic Combination

Yanping Qin, Jun Zhang, Huaqiong Duo

The Journal of Grey System 2025, 37 (1): 118-132.

摘要（196）

Wood defects affect the use value and commodity value of wood, so the research on effective recognition of wood defects has important practical significance. In this study, three types of wood defect images (live knots, cracks, and dead knots) were used as research objects. To investigate the impact of edge detection and characteristics combination on recognition rate, the recognition method based on threedimensional grey absolute relational grade (TGARG) is constructed and the recognition rates of different types of wood defects were compared under different edge detection and characteristics combinations. The results show that, based on TGARG, the recognition rate of live knots is the highest (0.76) under edge detection by Canny operator as well as characteristics combination of energy and homogeneity. The recognition rate of cracks is the highest (1.00) under edge detection by Roberts or Sobel operator as well as characteristics combination of contrast and correlation. The recognition rate of dead knots is the highest (0.90) under without edge detection as well as characteristics combination of correlation, energy and homogeneity. The research method and conclusion proposed in this study on the selection of wood defect recognition from a new perspective will contribute to the development of wood defect recognition.

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13. Evaluation of Barriers to Disabled Elderly’s Access to eHealth in China Using Grey Relational Analysis

Muhammad Nawaz, Sifeng Liu, Naiming Xie, Mohammed Atef, Muhammad Wasif Hanif

The Journal of Grey System 2024, 36 (5): 1-14.

摘要（192）

This study aimed to identify and rank the barriers faced by disabled elderly in China while accessing eHealth primary care services. Primary data were collected from the disabled elderly based on technological, individual, relational, environmental, and organizational constructs. The Dynamic Grey Relational Analysis (DGRA) and Multiple-criteria Decision-making (MCDM) based TOPSIS techniques were used to identify and rank the barriers. We found that the most significant barrier was “aging limitation (reduction in hearing, sight, memory, and fine motor control)” in both (DGRA and MCDM) cases. The Kruskal-Wallis test was used to investigate the significance of this barrier in different age groups of disabled elderly. We found no significant differences among the three age groups of disabled elderly, which shows that the barrier “aging limitation (reduction in hearing, sight, memory, and fine motor control)” is the most significant barrier at each age group (when age ≥ 60) of disabled elderly. The average value of Grey Relational Grades (GRGaverage) and the sorting outcomes of the MCDM of the construct individual were higher than those of all other constructs. This study is the first of its kind to apply the DGRA, MCDM and KWT to expose the barriers while accessing eHealth services for the disabled elderly in China.

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14. Prediction of Digital Economy Development Levels in Urban Cities Based on the GCSA-GM(1,N) Model

Chengxuan Wu, Cheng Tian, Fang Wang, Wenxin Cheng

The Journal of Grey System 2024, 36 (4): 69-77.

摘要（190）

Based on the digital economy index (DEI) and Technological Innovation, Industrial Structure, GDP and Openness to the Development Index data of 15 sub-provincial cities from 2017 to 2021, we construct a framework to predict the development potential of the urban digital economy and analyse the spatial evolution trend under the ‘small data’ scenario using geometric causal strength analysis GM(1,N) and the gravity center model. The empirical analysis reveals that,15 sub-provincial cities, at least one of the influencing factors has a causal relationship with the urban DEI that is greater than 0.5. The average forecast error of the GM(1,N) model based on causality strength in 15 sub-provincial cities is less than 1% in 2022. This reflects that four influencing factors can be used as an effective indicator to measure the level of digital economic development. The forecast results also indicate that the digital economy center of China’s sub-provincial cities will evolve from north to south and from east to west in 2022-2025. Finally, this study presents suggestions from three aspects: Strengthening technological innovation, promoting industrial digital transformation and upgrading, and strengthening cross-regional cooperation and exchanges.

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15. A Flexible Time Power Grey Fourier Model for Nonlinear Seasonal Time Series and Its Applications

Xiaomei Liu, Jiannan Zhu, Meina Gao

The Journal of Grey System 2025, 37 (1): 47-63.

摘要（179）

Grey Fourier model has been successfully applied in seasonal time series forecasting, but its performance in handling nonlinear seasonal time series may still require further improvement. To describe the nonlinear characteristics, a flexible time power grey Fourier model (TPGFM(1,1,N,r)) is proposed by introducing nonlinear time power terms to the grey action of grey Fourier model. The hyperparameters, the truncated Fourier order N and time power r are initially selected by the Nyquist-Shannon sampling theorem and the principle of simplicity, then the optimal parameters are determined by the hold-out method. To further improve the prediction accuracy for nonlinear time sequences, combination models based on the proposed grey model, statistical models and artificial intelligence models are designed. The variable weights are assigned by the inverse variance weighting method. Afterward, the results of the designed experiments based on numerical experiment verify the validity of the Fourier order and time power selection, illustrating the superior performances over benchmark models. Finally, the proposed model is applied for monthly PM2.5 forecasting and quarterly wind power generation forecasting, outperforming other benchmark models in prediction, including seasonal grey models, artificial intelligence models and statistical models. Moreover, the combination models, developed based on TPGFM(1,1,N,r) model, have achieved higher prediction accuracy.

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16. Construction of Symbiosis System for Rural Industry Revitalization Based on Lotka-Volterra Model and Stability Strategy Study

Na Zhang, Shuting Shi, Zihao Li

The Journal of Grey System 2024, 36 (4): 33-54.

摘要（164）

The symbiotic system of rural industrial revitalization comprises farming households, grassroots governments, and new rural collective economies as symbiotic units. The optimal symbiosis mode within this symbiotic system is reciprocal symbiosis. This study focuses on Yuhang District in Zhejiang Province, Yining County in Xinjiang Uygur Autonomous Region, and Wangcheng District in Hunan Province as research areas. Firstly, the grey Lotka-Volterra (GLV) model is employed to analyze the interaction within the current symbiotic system of rural industrial revitalization across these regions using data from 2019-2023. Secondly, this paper utilizes the GM(1,1) model to predict future data for these regions and analyze their future symbiosis. Subsequently, this paper examines the equilibrium point and stability of the symbiosis systems within these regions. Finally, based on an evolutionary game model approach, key factors influencing the evolution of a stable symbiosis system when satisfying and balancing interest demands among symbiotic units are explored. The findings reveal distinct characteristics within each subject's rural industrial revitalization symbiotic system. Government subsidies' intensity and cooperation benefits and costs primarily influence its evolution towards stability.

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17. A Novel Grey Multi-attribute Three-way Decision Model Under Risk Preferences

Yu Qiao, Lirong Jian, Yong Liu, Xu Wang

The Journal of Grey System 2025, 37 (1): 16-32.

摘要（156）

To address multi-attribute decision making problems where attribute values are interval grey numbers with partial weight information known, this study considers decision-makers’ risk preferences and integrates three-way decision theory to propose a novel grey multiattribute three-way decision model under risk preferences. Initially, in grey information systems lacking category labels and decision attributes, this model incorporates risk preferences to convert interval grey number-based evaluation values into corresponding real numbers, thereby quantifying decision information under uncertain conditions. Subsequently, grey relational analysis is employed to objectively determine conditional probabilities, significantly reducing subjective bias in decision-making. Furthermore, the model analyzes the relationship between evaluation values and loss functions, deriving a relative loss function matrix in interval grey number form, thus enhancing data reference value and improving model reliability. Building on this, this study establishes multi-attribute threeway decision rules suitable for grey environments based on risk preferences and explores the related theories of the new model. Finally, the new model is applied to the supplier selection issue, and its effectiveness, superiority, and stability are verified from multiple perspectives through comparative and experimental analysis.

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18. Assessing the Service Quality of Fisherman's Homestays in China: a Hybrid MADM Approach Consisting of DANP and Grey Clustering Evaluation

Peng Jiang, Rui Chi, Hui Xia, Longyun Zhang, Chuandong Ju

The Journal of Grey System 2024, 36 (4): 90-110.

摘要（155）

Nowadays, a new emerging tourism industry, named fisherman's homestay, has become a very representative marine leisure tourism project, widely promoted in coastal areas in China. However, the development of China's fisherman's homestay industry is not yet mature and there are many problems, such as incomplete laws and regulations, lack of infrastructure, and severe homogenization. Therefore, it is very important to help the owners of fisherman's homestay improve the service quality. Based on the Service Quality Gap Model, this paper establishes an evaluation index that affects the service quality of fishermen's homestay. We apply decisionmaking trial and evaluation laboratory-based analytic network process (DANP) to identify the critical factors and the causal relationship between them. And the grey clustering model is used to evaluate the service quality of Liaoning province and other five places. Experimental results reveal those six factors, including surrounding facilities, online marketing, room infrastructure, personalized service, community co-prosperity, and attention to harmonization with the environment, contribute to improving the service quality of fisherman's homestays. The fisherman's homestays in Shandong Province, Liaoning Province, and Zhejiang Province are in "excellent" level, and the fisherman's homestays in Fujian Province and Guangxi Zhuang Autonomous Region are in "good" level.

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19. Multivariate Forecasting of Seasonal Carbon Dioxide Emissions via a Discrete Grey Multivariate Forecasting Model with a New Information Priority Accumulation Operator

Jianming Jiang, Yandong Ban, Ming Zhang, Chiwen Qu

The Journal of Grey System 2024, 36 (6): 69-78.

摘要（152）

In this study, a more efficient Discrete Grey Multivariate Forecasting Model with A New Information Priority Accumulation Operation is proposed to depict the development trend of energy-related seasonal carbon dioxide emissions. The new information priority accumulation operation and an adaptive grey action quantity in the new model ensure excellent nonlinear fitting capabilities. The presence of the virtual variable allows the model to directly simulate seasonal fluctuations in seasonal carbon dioxide emissions without removing seasonal effects, showcasing the model's superiority. Therefore, the model can fit the nonlinear seasonal time series better. Experiments based on quarterly carbon dioxide emissions from energy consumption in the United States demonstrate the new method's optimal forecasting performance. Additionally, the optimization capability of each component in the new model is further validated by a more in-depth experiment. The effectiveness of this method in fitting seasonal carbon dioxide emissions is confirmed.

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20. Maintenance Modeling and Grey Lease Pricing for a Series Manufacturing System with the Machines from Multiple Suppliers

Yaping Li, Yuhong Cheng, Tangbin Xia, Zhen Chen, Naiming Xie, Ershun Pan

The Journal of Grey System 2024, 36 (4): 14-25.

摘要（150）

Leasing is an important mode of service-oriented manufacturing where a manufacturer may lease machines from multiple suppliers to form a manufacturing system. While the suppliers provide machine maintenance, their individual interests may not be necessarily optimal to the system. Therefore, we propose a maintenance modeling and lease pricing (MMLP) framework to find the optimal maintenance policy for the system, and make a lease pricing scheme as an incentive mechanism to promote the realization of the cooperative maintenance among the suppliers. An optimization model is established to obtain a long-term maintenance policy by minimizing a cost rate function. And then, the grey lease pricing scheme based on the fair allocation of the benefits from the cooperation is suggested, with the marginal contribution of each supplier in the cooperation measured by the grey Shapley value method. Finally, a case study is used to show the application of the MMLP framework, presenting that the joining of the suppliers can make maintenance cost reduced and that the lease prices determined by using the grey Shapley value demonstrate the emergence and risk of the cooperation.

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