考虑二次优势判别的动态竞优评价方法及应用
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摘要
针对动态综合评价中难以判别个性化优势和权重确定"重近轻远"的问题,提出了一种考虑二次优势判别的动态竞优评价方法。采用竞优理论中的个性化优势判别法确定客体的各指标权重;据此构建比较优势评价模型,对其各评价结果求解算术平均数,确定民主优势评价值;随后对民主优势评价结果进行二次个性化优势判别,并计算客体的动态个性化权重;进一步建立和求解动态的自下而上比较优势评价模型和自上而下的民主优势评价结果。此外,以一个应用算例来验证该方法的有效性和优越性。
In this research, a dynamic evaluation method on better action conforming to natural rules considering twice identification of advantage is proposed to solve the individual advantage weight and laying more stress on the present information on the past problem in dynamic comprehensive evaluation. In this method, firstly, the weights of evaluated objects are calculated using the individual advantage identifying method from the theory of better action conforming to natural rules. Then, according to the identified results, the competitive advantage evaluation is set and the average information for each outcome is to make democratic advantage consequence. Furthermore, the democratic advantage result of the evaluated objects is calculated the second time by the method of individual identification, which outputs the dynamic individual weights of the evaluated objects. Moreover, the optimal bottom-up approach of dynamic competitive advantage evaluation and from top to bottom dynamic democratic advantage assessment are determined by establishing and solving the evaluation model. Finally, an example of the real situation is used to justify the proposed method for effectiveness and superiority.
In this research, a dynamic evaluation method on better action conforming to natural rules considering twice identification of advantage is proposed to solve the individual advantage weight and laying more stress on the present information on the past problem in dynamic comprehensive evaluation. In this method, firstly, the weights of evaluated objects are calculated using the individual advantage identifying method from the theory of better action conforming to natural rules. Then, according to the identified results, the competitive advantage evaluation is set and the average information for each outcome is to make democratic advantage consequence. Furthermore, the democratic advantage result of the evaluated objects is calculated the second time by the method of individual identification, which outputs the dynamic individual weights of the evaluated objects. Moreover, the optimal bottom-up approach of dynamic competitive advantage evaluation and from top to bottom dynamic democratic advantage assessment are determined by establishing and solving the evaluation model. Finally, an example of the real situation is used to justify the proposed method for effectiveness and superiority.
引文
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[20] 张莉莉,胡祥培.基于人力资本竞优结构的“团队-作业对象”匹配决策模型[J].管理工程学报,2015,29(1):1-7.
[21] 司岩.理想点效用模式下的主旋律分析方法及求解[J].东北大学学报(自然科学版),2016,37(9):1359-1363.
[22] 张兰霞,付竞瑶,姜海滔,等.我国区域中心城市科技人力资源竞争力评价[J].东北大学学报(自然科学版),2016,37(2):290-294.
[23] 贾建锋,柳森,赵希男.研究型大学教师团队成员胜任特征的匹配研究[J].科研管理,2017,38(1):118-126.
[24] 贾明媚,张兰霞,付竞瑶,等.基于竞优评析的高层次科技人才评价[J].科技进步与对策,2017,24(14):1- 6.
[25] Ahmed Z, Ramakrishnan S, Noreen U. Financial literacy as competitive advantage for individual investors’ decision making[J]. Journal of Computational & Theoretical Nanoscience, 2017, 23(9): 8988- 8993.
[26] 罗瑾琏,徐振亭,钟竞.个体创造力的跨层次影响因素:个体目标取向与团队自省[J].科技进步与对策,2016,33(4):138-143.
[27] 赵希男,汤良.面向个体优势识别的区间直觉模糊综合评价[J].运筹与管理,2016,25(6):190-194.
[28] 刘宏涛,赵希男.基于客体优势识别的自主式竞优评析方法[J].运筹与管理,2017,26(3):131-137.
[29] 童爱香,张红,孙艳艳,等.北京、上海、深圳、广州科技创新能力比较[J].科技管理研究,2017,37(3):100-107.
[2] 王德青,朱建平,王洁丹.基于自适应权重的函数型数据聚类方法研究[J].数理统计与管理,2015,34(1):84-92.
[3] 郝晶晶,朱建军,刘远.双重信息下多阶段异质群体决策模型及算法[J].系统工程,2016,34(5):129-135.
[4] 王斌,李刚,彭晓红,等.基于一致性排序的动态评价方法研究[J].数学的实践与认识,2017,47(13):33-39.
[5] 赵希男,刘炳东,许慧敏.竞优思想及其对人类进步的作用分析[J].科学技术哲学研究,2006,23(2):32-35.
[6] Liu W W, Shi C S, Zhao S B. Dynamic comprehensive evaluation model with the feature of speed[J]. Systems Engineering-Theory & Practice, 2013, 33(3): 705-710.
[7] West R E, Williams G, Williams D. Improving problem-based learning in creative communities through effective group evaluation[J]. Interdisciplinary Journal of Problem-based Learning, 2013, 7(2): 102-127.
[8] Ding L, Shao Z, Zhang H, et al. A comprehensive evaluation of urban sustainable development in China based on the topsis-entropy method[J]. Sustainability, 2016, 8(8): 745-768.
[9] 张发明,刘志平.组合评价方法研究综述[J].系统工程学报,2017,32(4):557-569.
[10] 郭亚军.综合评价理论、方法与拓展[M].北京:科学出版社,2012.
[11] 李美娟,陈国宏.基于漂移度的动态组合评价方法研究[J].中国管理科学,2015,23(1):141-145.
[12] 廖志高,詹敏,徐玖平.物元法分类动态综合评价方法及速度特征分析[J].中国管理科学,2015,23(11):119-127.
[13] 易平涛,周义,郭亚军,等.一种体现发展趋势的动态综合评价方法[J].运筹与管理,2016,25(6):175-180.
[14] 陈伟,李金秋,杨早立.基于误差传递和隶属度的动态灰靶多属性决策[J].系统管理学报,2017,26(6):1034-1042.
[15] 郭亚军,周莹,易平涛,等.基于全局信息的动态激励评价方法及激励策略[J].系统工程学报,2017,32(2):282-288.
[16] Li S. IT outsourcing service provider dynamic evaluation model and algorithms based on rough set[J]. International Journal of Computer Science Issues, 2013, 10(1): 236-241.
[17] Guo S, Liu S, Fang Z, et al. Multi-phase information aggregation and dynamic synthetic evaluation based on grey inspiriting control lines[J]. Grey Systems Theory & Application, 2014, 4(2): 154-163.
[18] 柳森,贾建锋.高新技术企业R&D人员绩效评价方法及实证研究——基于层次结构的个体优势特征识别视角[J].科学学与科学技术管理,2014,35(4):171-180.
[19] Huang S T, Zhao X N, Chang S, et al. Organizational construction of a new type of university scientific research team based on jingyou thought[J]. Eurasia Journal of Mathematics, Science and Technology Education, 2017, 13(8): 5615-5627.
[20] 张莉莉,胡祥培.基于人力资本竞优结构的“团队-作业对象”匹配决策模型[J].管理工程学报,2015,29(1):1-7.
[21] 司岩.理想点效用模式下的主旋律分析方法及求解[J].东北大学学报(自然科学版),2016,37(9):1359-1363.
[22] 张兰霞,付竞瑶,姜海滔,等.我国区域中心城市科技人力资源竞争力评价[J].东北大学学报(自然科学版),2016,37(2):290-294.
[23] 贾建锋,柳森,赵希男.研究型大学教师团队成员胜任特征的匹配研究[J].科研管理,2017,38(1):118-126.
[24] 贾明媚,张兰霞,付竞瑶,等.基于竞优评析的高层次科技人才评价[J].科技进步与对策,2017,24(14):1- 6.
[25] Ahmed Z, Ramakrishnan S, Noreen U. Financial literacy as competitive advantage for individual investors’ decision making[J]. Journal of Computational & Theoretical Nanoscience, 2017, 23(9): 8988- 8993.
[26] 罗瑾琏,徐振亭,钟竞.个体创造力的跨层次影响因素:个体目标取向与团队自省[J].科技进步与对策,2016,33(4):138-143.
[27] 赵希男,汤良.面向个体优势识别的区间直觉模糊综合评价[J].运筹与管理,2016,25(6):190-194.
[28] 刘宏涛,赵希男.基于客体优势识别的自主式竞优评析方法[J].运筹与管理,2017,26(3):131-137.
[29] 童爱香,张红,孙艳艳,等.北京、上海、深圳、广州科技创新能力比较[J].科技管理研究,2017,37(3):100-107.