Evaluation Model For Selection Research Articles

Evaluation model of green supplier selection for coal enterprises with similarity measures of double-valued neutrosophic sets based on cosine function

Coal is a vital basic energy source for any economy in the world, and our country is no exception. Our coal resources are abundant, with high production and demand, not comparable to oil and natural gas. The coal supply chain plays an equally important role in economic production, but unfortunately, the current coal supply chain is not focused on greening while creating profits. Unfortunately, the current coal supply chain does not focus on green production and energy conservation and emission reduction while creating profits, which has caused irreversible harm and loss to resources and environment. This has caused irreversible damage and loss to resources and the environment. The green supplier selection for coal enterprises is affirmed as multiple attribute decision making (MADM). In such paper, motivated by the idea of cosine similarity measure (CSM), the CSMs are extended to DVNSs and four CSMs are created under DVNSs. Then, two weighted CSMs are built for MADM under DVNSs. Finally, a numerical example for Green supplier selection for coal enterprises is affirmed and some comparative algorithms are produced to affirm the built method.

Exploring the critical factors influencing the outlying island talent recruitment and selection evaluation model: Empirical evidence from Penghu, Taiwan

The declining birth rate, population ageing and the outbound migration of young people in recent years have created obstacles for local companies in recruiting skilled personnel. Similar factors have also affected recruitment in the outlying island of Penghu, Taiwan. Multiple-attribute decision-making (MADM) techniques for evaluation model development were incorporated in the present research to investigate the key determinants of talent recruitment by the coffee house operators in the outlying island of Penghu. The decision-making trial and evaluation laboratory (DEMATEL) approach was first implemented to (i) examine the extent of mutual impact between evaluation predictors and (ii) develop an influential network relation map (NRM) for indicator and sub-indicator assessments. Subsequently, the DEMATEL-based analytic network process (DANP) technique was utilised to compute the weights of every indicator and sub-indicator. Additionally, the modified VlseKriterijumska Optimizcija I Kaompromisno Resenje or VIKOR (in Serbian) approach evaluated every indicator and sub-indicator performance gap for empirical data analysis with suggested conclusions and recommendations. The results showed that the first dimension that should be improved is past experience, followed by personality traits and professional competence, according to the causal diagram of the NRM. The weights acquired through the DANP indicated that professional competence was the most influential dimension, followed by personality traits, whereas past experience was the least influential. Past experience revealed that the highest gap value is the most important for development if coffee house operators want to attain the appropriate levels. Finally, the theoretical, managerial, and practical implications were discussed. Notably, the research outcomes could optimise talent recruitment, establish appropriate talent recruitment methods for coffee house operators, and enhance the human resource quality in the outlying island of Penghu.

Modeling Methodology for Site Selection Evaluation of Underground Coal Gasification Based on Combination Weighting Method with Game Theory.

The lack of systematic geological work is an essential reason why underground coal gasification (UCG) has not been industrialized for a long time. Building a scientific index system and favorable area evaluation technology for the UCG site selection is the key to breaking through the geological bottleneck. Aiming at the problems of the single index weight determination method, intense subjectivity, and poor reliability of current evaluation models, we put forward an evaluation modeling methodology for the UCG site selection using the combination weighting method with the game theory. The factors of coal resource conditions associated with the potential risk of UCG are systematically analyzed. From the six dimensions of the geological structure, hydrogeology, seam occurrence, coal properties, reserves, and roof lithology, 23 key factors were selected as evaluation indexes to construct a hierarchical model composed of the target layer, category index layer, and index layer. The influence of each index on UCG and its reasonable value range were systematically analyzed. The evaluation index system for UCG site selection was formed. The improved analytic hierarchy process (AHP) was adopted to sequence indices and determine their subjective weight. And the variability, conflict, and information amount of the index data were analyzed by the CRiteria Importance Through Intercriteria Correlation (CRITIC) method to calculate the objective weight. Then, the subjective and objective weights were combined through game theory. On this basis, fuzzy theory was employed to calculate the membership of indices and construct the fuzzy comprehensive judgment matrix. The evaluation model of the UCG site selection was applied to the suitability evaluation of resource conditions of UCG pilot projects at Zhongliangshan (ZLS), Huating (HT), and Shanjiaoshu (SJS) mines in China. The result shows that the resource conditions of HT are the best, followed by ZLS and, finally, SJS, which are consistent with the actual running effects of the three UCG pilot projects. It indicates that the evaluation model can provide a scientific theoretical basis and reliable technical support for the UCG site selection.

An Evaluation and Ranking Model for Agricultural Suppliers Selection

An Evaluation and Ranking Model for Agricultural Suppliers Selection

An improved evaluation model for supplier selection based on particle swarm optimisation‐back propagation neural network

With the trend of supply chain globalisation, competition among enterprises is becoming more intense. Enterprises urgently need to improve their core competitiveness, and the enhancement of the competencies can depend on technologies services and the quality of suppliers. Since external factors are less controllable, this study starts with the quality of suppliers and proposes a supplier evaluation method that combines particle swarm optimisation with neural network algorithm to maximise the interests of enterprises. The particle swarm algorithm to lock the approximate location of the global optimum is first employed. Based on this, we establish an evaluation model of suppliers to train for the minimum errors between the desired and predicted values by constructing a back propagation (BP) neural network. Finally, the output results of the proposed method is compared with the BP neural network without the particle swarms optimisation. The proposed model is less empirically sensitive to the initialisation and can quickly converge to the local optimums, which overcomes the shortage of traditional neural networks and is more applicable to supplier evaluation.

A Hybrid FMCDM Approach for the Evaluation and Selection of Homestays.

Due to the beautiful rural scenery, rural tourism has gradually become a popular trend as affected by urbanization in Taiwan. The purpose of this study is to develop an objective and systematic evaluation model for homestay selection in Taiwan. Specifically, this study combines three fuzzy multiple-criteria decision-making (FMCDM) methods of means-end chain (MEC), fuzzy decision making and trial evaluation laboratory (FDEMATEL), and fuzzy analytic hierarchy process (FAHP). First, we use MEC to obtain important factors for homestay travelers to choose homestays, then we extract key influencing factors by FDEMATEL method, and finally, we rank these factors in importance by FAHP to provide travelers and managers with a reference. In addition, this study combines fuzzy theory to avoid the bias caused by human subjective judgment, so as to solve the problem of objectivity in the selection and evaluation model of homestay criteria. According to the results of our case studies, a clean environment, professional service staff, safe facilities and beautiful buildings are the key factors for consumers to choose homestays. The results of this study can provide a reference for homestay managers to understand the priorities of travelers and optimize customer service in Taiwan.

Constructing a framework for selecting natural fibres as reinforcements composites based on grey relational analysis

Abstract Material selection is crucial in product development, especially when material from a composites process application is involved. Numerous multi-criteria decision-making (MCDM) tools each have their own set of advantages and disadvantages. Using grey relational analysis (GRA), this research proposes a systematic framework evaluation approach for generating a sensible rank for material selection of natural fibre as reinforcement composites. The framework was created using the GRA technique, a robust evaluation tool that employs the grade of relation to determine the degree of similarity or difference between two sequences. The MCDM approach can be straightforward for the material selection problem. A GRA technique is used to investigate the performance of the potential material, which includes grey relational sequence creation, reference sequence definition, grey relational coefficient calculation and grey relational grade determination. This framework is applied with a case study to identify the optimum natural fibres composites material for a bike helmet. End results revealed that pineapple is the best candidate for construction of safety gear (cyclist helmet). The best possible evaluation model for material selection of the composite can be referred by design engineer in composite industry for multiple applications. Moreover, the proposed framework is an aid to help engineers and designers to choose most suitable material.

An Entropy Weight-TOPSIS Based Model for Partner Selection of Strategic Alliance of Prefabricated Construction Enterprises

Selecting the right partner is a key factor for the successful construction of the strategic alliance of prefabricated construction enterprises in China. Based on the summarization of domestic and foreign studies, combined with the characteristics of the strategic alliance of prefabricated construction enterprises, the paper has constructed an evaluation indicator system of the partner selection of the strategic alliance of prefabricated construction enterprises in China. The paper also has conducted an empirical study on the evaluation model of partner selection of the strategic alliance of prefabricated construction enterprises in China by using the method Entropy Weight-TOPSIS. The research results show that the five most influential second-level indicators are commercial housing sales capability, property management capability, commitment of capital, commitment of talents, and product innovation capability. The model constructed in the paper can comprehensively evaluate and select the strategic alliance partners of prefabricated construction enterprises in China.

Multi-method combination site selection of pumped storage power station considering power structure optimization

Energy internet (EI) is the framework foundation for tackling climate change and environmental issues and achieving “carbon peak and carbon neutral”. In this paper, considering the important function of pumped-storage power station (PPS) in promoting the “source-grid-load-storage” synergy and complement in the construction of EI, a novel evaluation index system and evaluation model for the site selection of PPS is proposed to provide decision support for the orderly construction of EI. Firstly, compatible with traditional engineering construction factors and multi-energy complementary needs, a systematic evaluation index system of PPS site selection is established from hydrological conditions, topographical and geological conditions, construction conditions, power grid development planning and economic and environmental benefits. Secondly, considering the inconsistency of conclusions of a single evaluation method, the cycle elimination mechanism based on Kendall’s concordance coefficient (KCC) is introduced into the combination evaluation model of PPS site selection, and the validity measurement method of the model is defined. Finally, a case study on the site selection of PPS in Hebei province of China is carried out to verify the effectiveness of the combination evaluation model, and the sensitivity analysis is carried out. The research shows that it is highly feasible to use the index and model constructed in this paper for the site selection of PPS. The combination evaluation model based on cycle elimination solves the inconsistency of the evaluation conclusions and greatly improves the effectiveness of the combination evaluation model.

Site selection of self-driving and recreational vehicle camps in China: An investigation using analytic hierarchy process and entropy

Self-driving and recreational vehicle (RV) camps are a new form of industry module with the integration of transportation and tourism in China, thus the scientific and reasonable site selection plays an important role in the success of camps’ construction and operation. In terms of relying resources and development factors, camps can be divided into five categories: scenic-spot-based, transportation-based, environment-based, project-based and leisure and vacation-based. According to whether it is of excludability and competitiveness, the camps in China mainly embody the attribute of private products. Based on the combination of subjective evaluation and objective calculation, the evaluation model of spatial site selection is constructed and the weight of each index is calculated by using analytic hierarchy process (AHP) method and entropy coefficient method. The results show that traffic condition factor is the priority to the selection of campsite, and whether it is on the popular main self-driving route and the grade of trunk roads are the dominant indices. The second factor taken into consideration is the social factors, in which government policy supports and land cost play a key role. The third factor is the market, in which the urban economic level, partnership with the government and tourist resource conditions are of great importance. The fourth factor of the campsite selection includes natural elements, in which the quality of ecological environment and water source conditions are mostly considered. In the future, it is suggested that a camp pattern of “public goods” plus “private goods” should be built and the construction of camps in underdeveloped areas should be highly developed so as to form camp spatial network from individual points to a series of campsite and finally the campsite group in China will be set up. • According to excludability and competitiveness of public goods theory, camps embody the attribute of private products. • The evaluation model of site selection which includes 20 indices of market factors, traffic factors, natural factors and social factors is constructed. • The index weight of site selection is calculated by the combination of subjective AHP and objective entropy method.

Model construction for field operation machinery selection and configuration in wheat-maize double cropping system

In order to scientifically and reasonably select the field operation machinery in wheat-maize double cropping system, first, the selection evaluation index system was constructed through the existing national standards and industry standards. Then the selection evaluation model was established based on the improved fuzzy comprehensive evaluation method. And the method of subjective weight and objective weight was used to overcome the drawbacks of the previous single weighting method that could not take into account the subject and object information of each indicator, and the weight value of each index was obtained in the evaluation system. Finally, the tillage process was used as an example, the field experiment was carried out to obtain the evaluation index value, and the model of selection evaluation was verified. The selection results of moldboard plough and rotary cultivator were as follows: the order of the comprehensive evaluation results of the moldboard plough results was ranked from high to low as 1LFK-435 (IIM), 1LFK-535 (IM), 1LF-342 (IIIM), 1LFT-445 (IVM), 1LFT-545 (VM), and the best machine type of the moldboard plough was IIM; the order of the comprehensive evaluation results of the rotary cultivator was ranked from high to low as 1GQKGN-240 (IIIR), 1GKNSM-250 (IVR), 1GKN-230K (IR), 1GKN-250K (IIR), 1GQKGN-220 (VR), and the optimal model of the rotary cultivator was IIIR. The experimental results showed that the results obtained by the evaluation model were in agreement with the local actual situation. The evaluation model will provide a scientific method for the selection of wheat and maize double cropping field operation machinery. Keywords: wheat-maize double cropping system, agricultural machinery, parts selection mode, evaluation system, fuzzy comprehensive evaluation method, combination weight DOI: 10.25165/j.ijabe.20211404.6383 Citation: Zhang F, Chen T H, Teng S, Wang J J, Xu R L, Guo Z J. Model construction for field operation machinery selection and configuration in wheat-maize double cropping system. Int J Agric & Biol Eng, 2021; 14(4): 82–89.

Research on Supplier Selection of Prefabricated Building Elements from the Perspective of Sustainable Development

Prefabricated building is an efficient building mode. Compared with the traditional building mode, the prefabricated building has advantages of less pollution, high construction efficiency, being more labor-saving, and economy, which is in line with China’s sustainable development strategy. This paper proposes a supplier selection evaluation model based on the mechanism equation model (SEM) and intuitionistic fuzzy analytic hierarchy process (IFAHP). Based on a detailed literature review, 300 structured questionnaires were distributed to the relevant enterprises, and an evaluation index system of prefabricated building element suppliers was built. With the fitting and modification process using a structural equation model, and assist of a path factor, an evaluation index system for evaluating the prefabricated building element suppliers was finally obtained. Finally, the intuitionistic fuzzy analytic hierarchy process was used to establish a selection model of prefabricated element suppliers, and the prefabricated element suppliers of Shuangyashan prefabricated construction projects were analyzed as a case study. The results show that the following factors have the most significant impact on supplier selection (from high to low): quality, economy, long-term cooperation, after-sales, and transportation. This study had a comprehensive consideration of the influencing factors existing in the whole selection process and should provide a valuable reference for the sustainable development of prefabricated construction engineering.

Economic evaluation of rock oil project based on AHP algorithm

In order to reveal the characteristics of oil shale, the distribution of oil shale and the potential of resources in Jianchang Basin. The selection evaluation model and index system of oil shale development are established in this process. The weight of each layer evaluation index is determined, and a unified scoring system is established to obtain the index value. The weighted summation obtains the comprehensive score of each target area. The results show that the most important factors affecting the assessment of oil shale development are the geological and resource conditions of oil shale ore spots and the key parameters are oil shale oil content, ore body depth, and shale oil resources. By using AHP to evaluate 5 oil shale exploration areas in Jianchang Basin, it can be determined that Daqingshan and Chaoyang Qidaoquanzi exploration areas in Aohan Banner have the highest score, the best exploration prospect, the stable profitability, and the strong profitability of the project. Strong ability to resist risks.

Applying the Multi-Criteria Decision-Making Approach for Lawyer Selection from Law Firms’ Perspective in China

This study proposes a novel evaluation model for lawyer selection incorporating the lawyer’s backbone leadership attitude employing the hybrid multi-criteria decision-making (MCDM) approach. In the proposed approach, the lawyer’s backbone leadership attitude is employed as an evaluation factor in the evaluation model for lawyer selection from law firms’ perspective. In this paper, a hybrid approach based on the Delphi technique and analytic hierarchy process (AHP) is proposed to manage qualitative and quantitative criteria for selecting the best alternative lawyer for law firms in China. Finally, a law firm in China is carried out to verify the feasibility of the proposed approach. Based on the result, the backbone leadership does provide valuable information in the evaluation model for lawyer selection. The results also revealed that the proposed approach would help law firms and human resource managers to understand and develop strategies to hire a lawyer.

Comprehensive evaluation model of wind farm site selection based on ideal matter element and grey clustering

China has carried out the relevant research on the evaluation of the wind farm site selection, but the evaluation index are mainly from the economic aspect and comprehensive benefit evaluation research of the wind farm site selection exists defects. In order to comprehensively to consider the explicit and implicit benefits of wind farms, firstly, a comprehensive evaluation index system for the wind farm site selection is established, which mainly includes economic, environmental and social aspects. Secondly, an integrated weight model with subjective and objective weight method is constructed, and the ideal matter element extension evaluation model and the grey clustering evaluation model for the wind farms site selection are proposed. Finally, case studies show that the proposed comprehensive evaluation model can rank the comprehensive benefits of wind farms site selection. Based on the comprehensive evaluation results of wind farm site selection, a comprehensive evaluation model of wind farm site selection is proposed to this paper, which can provide the decision basis of the decision makers. This paper establishes an index evaluation model from three aspects of economy, environment and society, examines the advantages and disadvantages of each access location of wind power system, so as to make a reasonable site selection. In view of the current development of the electricity market, this paper constructs a differential weighting model based on the built evaluation model for wind power system location. The simulation results show that the proposed model can effectively guide the location optimization of wind power system.

Evaluation and Selection Methods of Tourism Characteristic Town: The Case of Liaoning Province, China

The construction of a characteristic town is an important measure to promote the economic transformation and upgrading of China. It also promotes the coordinated and balanced development between urban and rural areas, and the construction of new urbanization and new rural areas. At present, China’s township governments are actively declaring construction projects of characteristic town. Considering the limitation of resources and funds, the government needs to choose projects with better foundation and better development prospects to invest and build, to avoid the waste of resources brought about by blind construction. Starting from the pre-selection of the construction projects of the characteristic town, taking Liaoning Province as an example, this research divided the characteristic town into four categories. Initially established the characteristic town evaluation index system blending comprehensive and multivariate index; then optimizes the index system through the statistical analysis, reliability analysis; and validity analysis of the questionnaire survey to finally obtain the selection index system of the construction projects of the characteristic town of Liaoning Province. Secondly, using the combination of Analytic Network Process (ANP) and Improved Technique for Order Preference by Similarity to an Ideal Solution (Improved-TOPSIS) method, the selection evaluation model of tourism-type characteristic town construction projects are obtained. Finally, taking the three tourism-type characteristic town projects declared by Liaoning Province as an example, using the ANP and Improved-TOPSIS evaluation model to evaluate and compare the three towns. The priority of “Xietun Town, Tanghe Town, Zhaoquanhe Town” is obtained. The result is consistent with the recommended order and verifies the applicability of the selection model. At the same time, through the feedback of the evaluation process, the current development constraints of the three towns are clarified, and the future development direction of the town is pointed out.

A new decision method for service supplier selection based on Choquet integral and generalized evidence theory

Service supplier selection is the most important problem in the process of service outsourcing. Aiming at the fuzziness of supplier evaluation index and subjectivity of decision-making process, a decision method for service supplier selection based on Choquet integral and generalized evidence theory is proposed. First, the fuzziness and uncertainty of information in decision-making process are solved by using interval rough number. The importance degree acquisition method of attribute index is corrected, and the relative weight and absolute weight of attribute index are obtained. Second, considering the interaction between attribute indexes, n-additive Choquet integral model is used to evaluate the service suppliers. According to the characteristics of service suppliers, the decision index system is proposed that is made up of different target variables, and the selection evaluation model of service supplier is established. Then, in order to eliminate the differences and conflicts of the expert evaluation opinions, the generalized evidence theory group decision-making method is introduced, and the expert evaluation opinions are fused so as to obtain the final result. Finally, a case study is provided to verify the validity and feasibility of the proposed method.

Establishing a Model for Evaluating Chicken Coccidiosis Resistance Based on Principal Component Analysis

Simple SummaryAvian coccidiosis, an infectious disease caused by seven species of Eimeria that can infect a bird’s digestive tract and significantly retard its growth, is a serious economic disease for chickens. Many studies have demonstrated that host resistance to coccidiosis related to genetic variations can be improved by selective breeding. The parameters for evaluation of resistance to coccidiosis could be objective indicators, such as body weight gain and cecal lesion score, or biochemical indices, such as immune factors or cytokines in the plasma or serum. The aim of the study is to establish an optimal comprehensive evaluation model including a resistance index that can be detected in live chickens (slaughter traits cannot be selected in breeding) based on principal component analysis. The value of individual chickens calculated with the optimal evaluation model is associated with the cecum lesion score; the larger the value, the stronger the resistance to coccidiosis. This illustrated that the optimal model is effective in coccidiosis resistance selection.To establish a coccidiosis resistance evaluation model for chicken selection, the different parameters were compared between infected and control Jinghai yellow chickens. Validation parameters were selected for principal component analysis (PCA), and an optimal comprehensive evaluation model was selected based on the significance of a correlation coefficient between coccidiosis resistance parameters and principal component functions. The following six different parameters were identified: body weight gain 3–5 days post infection and catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), malondialdehyde (MDA) and γ-interferon (IFN-γ) concentrations on the eight day post inoculation. Six principal components and one accumulated contribution of up to 80% of the evaluation models were established by PCA. The results showed that the first model was significantly or highly significantly related to nine resistance parameters (p < 0.01 or p < 0.05), especially to cecal lesions (p < 0.01). The remaining models were related to only 2–3 parameters (p < 0.01 or p < 0.05) and not to cecal lesions (p > 0.05). The values calculated by the optimal model (first model) were significantly negatively correlated with cecal lesion performance; the larger the value, the more resistant to coccidiosis. The model fi1 = −0.636 zxi1 + 0.311 zxi2 + 0.801 zxi3 − 0.046 zxi4 − 0.076 zxi5 + 0.588 zxi6 might be the best comprehensive selection index model for chicken coccidiosis resistance selection.

Subsea tunnel site selection evaluation: A new evaluation model

The foundation of subsea tunnel construction is that the expected benefit of the tunnel is greater than the construction cost. The location of subsea tunnels is the most fundamental factor determining the size of both tunnel revenue and cost. At present, the evaluation model for the site selection of subsea tunnels is mainly based on specific engineering projects, and the universal evaluation model for the subsea tunnels site selection is deficient. In this paper, nine parameters including lithology, geologic structure, rock strength, environmental conditions, economic benefit, construction cost, Minimum leakage method, Coal cutting experience under water method, and Norway experience method are selected as evaluation indexes for the site selection of subsea tunnels. The weight of each index is determined by weight back analysis. An evaluation model for subsea tunnel site selection is established based on weight back analysis method and efficacy coefficient method, and evaluation criteria are divided into four grades: excellent, good, medium, and bad. The evaluation model of subsea tunnel site selection is applied to the Qingdao Jiaozhou Bay subsea tunnel, the Xiamen Xiangan subsea tunnel, and the Seikan subsea tunnel. Results show that the site selection of the Qingdao Jiaozhou Bay subsea tunnel is grade II, the site selection of the Xiamen Xiangan subsea tunnel is grade III and the site selection of the Seikan subsea tunnel is grade IV. This new selection process provides a new method for subsea tunnel site selection and evaluation and also provides some reference for site selection of other types of structures.

A Fuzzy Based Trust Evaluation Model for Service Selection in Cloud Environment

Cloud computing is a popular computing paradigm among several computing environments, but a deficit in trust among the users and the service providers prevents the large adoption of the cloud in most of the businesses. Cloud service providers should give assurances for providing the reliable services to the cloud consumers. The proposed work explains about the architecture of the trust evaluation model and considered four service measurement indexes (SMI) namely: availability, success rate, turnaround efficiency and feedback about a resource. The trust value for each resource is estimated by the fuzzy evaluation engine in which a fuzzy input set is derived from the SMI parameters. By applying a fuzzy inference rule on fuzzy input sets will yield a fuzzy output set and finally, the most trusted resource value is calculated by defuzzification process called center of gravity. The proposed work is done the implementation by using cloudsim with jfuzzycloud.