半導體製造影響民生、經濟、國防日趨重大，己成為各國必爭的重要戰略產業。人才是半導體最重要的成功關鍵也是未來持續領先的核心要素。企業需維持每位員工好的總體薪酬水準、減少重複無挑戰性的工作以吸引高階人才，又需控制包含薪酬的整體成本以獲取利潤。勢必朝向以更少的人做到更大的產量、更大的營收和利潤努力，也就是人員生產力提升。
本研究的目的是針對半導體晶圓製造，建立人力規劃與生產力提升的管理架構。圍繞著提升人員生產力為目標，對人力資本管理建立規劃、執行、查核、行動的整體控制管理循環。人力資本問題往往不易數量化，本研究以紫式決策分析架構數量化地分析以提升人力資本。
本實證研究針對人員分派問題，找到方法將技能匹配與績效影響數量化，由組合問題觀點，考量人員組合的獨立、關聯、協同等組合效應，也都設計出可衡量的數值化指標。由於組合可能性極多，本研究利用基因演算法生成方案、TOPSIS法評估方案排序。並且以某半導體晶圓製造公司資材單位的人力分派為例，驗證可以考量多個目標，給出最佳方案，並以數值確認員工分派方案可以達到生產力提升之效果。

The semiconductor industry, driven by the evolution of semiconductor technology in accordance with Moore's law, has had a significant impact on various defense, economic, and daily life applications. It has become a strategically important industry worldwide. In this context, human capital plays a crucial role in the success and future of semiconductor manufacturing companies. However, the declining birth rate in Taiwan has affected the labor market, posing challenges for attracting and retaining talent. To address these challenges, semiconductor manufacturers need to offer competitive compensation packages and create a work environment that reduces repetitive and monotonous tasks. At the same time, they also need to focus on cost reduction, including salary costs, while increasing output and improving productivity.
This study proposes a framework for semiconductor human capital planning and enhancing productivity. The framework takes a holistic approach to address human capital challenges in semiconductor manufacturing companies. The framework adopts a PDCA (Plan-Do-Check-Act) management cycle with the goal of improving people productivity. This framework aims to quantitatively address human capital issues using the UNISON decision framework.
During the study, it was observed that staff assignment for productivity improvement was an area that received less attention. An empirical study was conducted, and the performance improvements resulting from skill matching were quantified. The study considered the independent, interrelated, and
synergistic effects of portfolio factors and quantified their impact. To handle the large number of possible solutions, a new generic algorithm was developed to generate alternatives, and the TOPSIS method was applied for ranking. The framework was validated using a logistics organization within a semiconductor manufacturing company, and it provided an optimal solution that effectively improved productivity. By implementing the UNISON Human Capital Planning and Control Framework, semiconductor manufacturers can take a proactive approach to address human capital challenges and enhance their overall productivity.

Al-Rawi, O. Y. M. and Mukherjee, T. (2019), "Application of linear programming in optimizing labour scheduling," Journal of Mathematical Finance, Vol. 9, No. 3, pp. 272-285.
Al Naimi, M., Faisal, M. N., Sobh, R., and Bin Sabir, L. (2022), "A systematic mapping review exploring 10 years of research on supply chain resilience and reconfiguration," International Journal of Logistics Research and Applications, Vol. 25, No. 8, pp. 1191-1218.
Albukhitan, S. (2020), "Developing digital transformation strategy for manufacturing," Procedia computer science, Vol. 170, No., pp. 664-671.
Andrews, D., Criscuolo, C., and Gal, P. N. (2016), "The best versus the rest: the global productivity slowdown, divergence across firms and the role of public policy," Vol., No., pp.
Attaran, M., Attaran, S., and Kirkland, D. (2019), "The need for digital workplace: increasing workforce productivity in the information age," International Journal of Enterprise Information Systems (IJEIS), Vol. 15, No. 1, pp. 1-23.
Augier, M. and Teece, D. J. (2009), "Dynamic capabilities and the role of managers in business strategy and economic performance," Organization science, Vol. 20, No. 2, pp. 410-421.
Balderas, F., Fernandez, E., Gomez, C., Cruz-Reyes, L., and Rangel V, N. (2017), "TOPSIS-grey method applied to project portfolio problem," in: P. Melin, O. Castillo, and J. Kacprzyk (eds.), Nature-inspired design of hybrid intelligent systems, Springer, Cham, pp. 767-774.
Banker, R. D., Charnes, A., and Cooper, W. W. (1984), "Some models for estimating technical and scale inefficiencies in data envelopment analysis," Management science, Vol. 30, No. 9, pp. 1078-1092.
Biebl, F., Glawar, R., Jalali, A., Ansari, F., Haslhofer, B., de Boer, P., and Sihn, W. (2020), "A conceptual model to enable prescriptive maintenance for etching equipment in semiconductor manufacturing," Procedia CIRP, Vol. 88, No., pp. 64-69.
Biswal, S. R. and Shankar, G. (2020), "Simultaneous optimal allocation and sizing of DGs and capacitors in radial distribution systems using SPEA2 considering load uncertainty," IET Generation, Transmission & Distribution, Vol. 14, No. 3, pp. 494-505.
Bloom, N., Ohlmacher, S. W., Tello-Trillo, C. J., and Wallskog, M. (2021). Pay, productivity and management, National Bureau of Economic Research.
Bluck, T., Smith, C., and Werbaneth, P. (2018), "Productivity Comparison of Wafer Transport Architectures in PVD Tools Used for Fan-Out Packaging RDL Barrier/Seed Formation," Proceedings of International Symposium on Microelectronics.
Bocken, N. M. and Geradts, T. H. (2020), "Barriers and drivers to sustainable business model innovation: Organization design and dynamic capabilities," Long range planning, Vol. 53, No. 4, pp. 101950.
Bohlouli, M., Mittas, N., Kakarontzas, G., Theodosiou, T., Angelis, L., and Fathi, M. (2017), "Competence assessment as an expert system for human resource management: A mathematical approach," Expert Systems with Applications, Vol. 70, No., pp. 83-102.
Brucker, P., Burke, E. K., Curtois, T., Qu, R., and Vanden Berghe, G. (2010), "A shift sequence based approach for nurse scheduling and a new benchmark dataset," Journal of Heuristics, Vol. 16, No. 4, pp. 559-573.
Brusoni, S., Prencipe, A., and Pavitt, K. (2001), "Knowledge specialization, organizational coupling, and the boundaries of the firm: why do firms know more than they make?," Administrative science quarterly, Vol. 46, No. 4, pp. 597-621.
Chen, L.-F. and Chien, C.-F. (2011a), "Manufacturing intelligence for class prediction and rule generation to support human capital decisions for high-tech industries," Flexible services and manufacturing journal, Vol. 23, No. 3, pp. 263-289.
Chen, W.-C. and Chien, C.-F. (2011b), "Measuring relative performance of wafer fabrication operations: A case study," Journal of Intelligent Manufacturing, Vol. 22, No., pp. 447-457.
Chen, Y.-H., Chen, C.-A., and Chien, C.-F. (2023), "Logistics and supply chain management reorganisation via talent portfolio management to enhance human capital and resilience," International Journal of Logistics Research and Applications, Vol., No., pp. 1-24.
Chien, C.-F., Chen, H.-K., Wu, J.-Z., and Hu, C.-H. (2007a), "Constructing the OGE for promoting tool group productivity in semiconductor manufacturing," International Journal of Production Research, Vol. 45, No. 3, pp. 509-524.
Chien, C.-F. and Chen, L.-F. (2008), "Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry," Expert Systems with applications, Vol. 34, No. 1, pp. 280-290.
Chien, C.-F., Chen, W.-C., and Hsu, S.-C. (2008), "An indirect workforce (re) allocation model for semiconductor manufacturing," Proceedings of 2008 Winter Simulation Conference.
Chien, C.-F., Chen, Y.-H., and Lo, M.-F. (2020), "Advanced Quality Control (AQC) of Silicon Wafer Specifications for Yield Enhancement for Smart Manufacturing," IEEE Transactions on Semiconductor Manufacturing, Vol. 33, No. 4, pp. 569-577.
Chien, C.-F., Chou, C.-W., and Yu, H.-C. (2016), "A novel route selection and resource allocation approach to improve the efficiency of manual material handling system in 200-mm wafer fabs for industry 3.5," IEEE Transactions on Automation Science and Engineering, Vol. 13, No. 4, pp. 1567-1580.
Chien, C.-F., Dou, R., and Fu, W. (2018a), "Strategic capacity planning for smart production: Decision modeling under demand uncertainty," Applied Soft Computing, Vol. 68, No., pp. 900-909.
Chien, C.-F. and Huynh, N.-T. (2018), "An integrated approach for IC design R&D portfolio decision and project scheduling and a case study," IEEE Transactions on Semiconductor Manufacturing, Vol. 31, No. 1, pp. 76-86.
Chien, C.-F., Kuo, H.-A., and Lin, Y.-S. (2022), "Smart semiconductor manufacturing for pricing, demand planning, capacity portfolio and cost for sustainable supply chain management," International Journal of Logistics Research and Applications, Vol., No., pp. 1-24.
Chien, C.-F., Wang, H.-J., and Wang, M. (2007b), "A UNISON framework for analyzing alternative strategies of IC final testing for enhancing overall operational effectiveness," International Journal of Production Economics, Vol. 107, No. 1, pp. 20-30.
Chien, C.-F., Wang, H.-K., and Fu, W. (2018b), "Industry 3.5 framework of an advanced intelligent manufacturing system: Case studies from semiconductor intelligent manufacturing," Management review, Vol. 37, No. 3, pp. 105-121.
Chien, C.-F., Zheng, J.-N., and Lin, Y.-J. (2014), "Determining the operator-machine assignment for machine interference problem and an empirical study in semiconductor test facility," Journal of Intelligent Manufacturing, Vol. 25, No., pp. 899-911.
Chien, C. F. (2002), "A portfolio–evaluation framework for selecting R&D projects," R&D Management, Vol. 32, No. 4, pp. 359-368.
Choi, Y. and Choi, J. W. (2020), "A study of job involvement prediction using machine learning technique," International Journal of Organizational Analysis, Vol., No., pp.
Costa, A., Fernandez-Viagas, V., and Framiñan, J. M. (2020), "Solving the hybrid flow shop scheduling problem with limited human resource constraint," Computers & Industrial Engineering, Vol. 146, No., pp. 106545.
Cruz-Reyes, L., Fernandez, E., Sanchez, P., Coello, C. A. C., and Gomez, C. (2017), "Incorporation of implicit decision-maker preferences in multi-objective evolutionary optimization using a multi-criteria classification method," Applied Soft Computing, Vol. 50, No., pp. 48-57.
Daft, R. L. (2015), Organization theory and design. Cengage learning, Mason.
De Bruecker, P., Van den Bergh, J., Beliën, J., and Demeulemeester, E. (2015), "Workforce planning incorporating skills: State of the art," European Journal of Operational Research, Vol. 243, No. 1, pp. 1-16.
Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. (2002), "A fast and elitist multiobjective genetic algorithm: NSGA-II," IEEE transactions on evolutionary computation, Vol. 6, No. 2, pp. 182-197.
Del Gatto, M., Di Liberto, A., and Petraglia, C. (2011), "Measuring productivity," Journal of Economic Surveys, Vol. 25, No. 5, pp. 952-1008.
Dessler, G. (2013), Human resource management, 13. Pearson, Boston.
Dutta, S., Biswal, M., Acharya, S., and Mishra, R. (2018), "Fuzzy stochastic price scenario based portfolio selection and its application to BSE using genetic algorithm," Applied Soft Computing, Vol. 62, No., pp. 867-891.
Edwards, W. (1977), "How to use multiattribute utility measurement for social decisionmaking," IEEE transactions on systems, man, and cybernetics, Vol. 7, No. 5, pp. 326-340.
Edwards, W. and Barron, F. H. (1994), "SMARTS and SMARTER: Improved simple methods for multiattribute utility measurement," Organizational behavior and human decision processes, Vol. 60, No. 3, pp. 306-325.
Ertogral, K. and Öztürk, F. S. (2019), "An integrated production scheduling and workforce capacity planning model for the maintenance and repair operations in airline industry," Computers & Industrial Engineering, Vol. 127, No., pp. 832-840.
Escolar-Jimenez, C. C., Matsuzaki, K., Okada, K., and Gustilo, R. C. (2019), "Data-driven decisions in employee compensation utilizing a neuro-fuzzy inference system," International Journal of Emerging Trends in Engineering Research, Vol. 7, No. 8, pp. 163.
Fernandez, E., Lopez, E., Mazcorro, G., Olmedo, R., and Coello, C. A. C. (2013), "Application of the non-outranked sorting genetic algorithm to public project portfolio selection," Information Sciences, Vol. 228, No., pp. 131-149.
Fjeldstad, Ø. D. and Snow, C. C. (2018), "Business models and organization design," Long range planning, Vol. 51, No. 1, pp. 32-39.
Fragapane, G., Ivanov, D., Peron, M., Sgarbossa, F., and Strandhagen, J. O. (2020), "Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics," Annals of operations research, Vol., No., pp. 1-19.
Fu, W. and Chien, C.-F. (2019), "UNISON data-driven intermittent demand forecast framework to empower supply chain resilience and an empirical study in electronics distribution," Computers & Industrial Engineering, Vol. 135, No., pp. 940-949.
Fu, W., Chien, C.-F., and Tang, L. (2020), "Bayesian network for integrated circuit testing probe card fault diagnosis and troubleshooting to empower Industry 3.5 smart production and an empirical study," Journal of Intelligent Manufacturing, Vol., No., pp. 1-14.
Goodwin, G. F., Blacksmith, N., and Coats, M. R. (2018), "The science of teams in the military: Contributions from over 60 years of research," American Psychologist, Vol. 73, No. 4, pp. 322.
Hart, O. and Moore, J. (2005), "On the design of hierarchies: coordination versus specialization," Journal of political Economy, Vol. 113, No. 4, pp. 675-702.
Haynes, B., Suckley, L., and Nunnington, N. (2017), "Workplace productivity and office type: An evaluation of office occupier differences based on age and gender," Journal of Corporate Real Estate, Vol., No., pp.
He, M. and Walheer, B. (2020), "Technology intensity and ownership in the Chinese manufacturing industry: A labor productivity decomposition approach," National Accounting Review, Vol. 2, No. 2, pp. 110-137.
Horrevorts, M., Van Ophem, J., and Terpstra, P. (2017), "Impact of cleanliness on the productivity of employees," Facilities, Vol., No., pp.
Hu, Y.-F., Hou, J.-L., and Chien, C.-F. (2019), "A UNISON framework for knowledge management of university–industry collaboration and an illustration," Computers & Industrial Engineering, Vol. 129, No., pp. 31-43.
Huang, Y.-Y., Li, L., and Tsaur, R.-C. (2022), "Smartphone market analysis with respect to brand performance using hybrid multicriteria decision making methods," Mathematics, Vol. 10, No. 11, pp. 1861.
Hutchcroft, P. D. (2001), "Centralization and decentralization in administration and politics: assessing territorial dimensions of authority and power," Governance, Vol. 14, No. 1, pp. 23-53.
Hwang, C.-L., Yoon, K., Hwang, C.-L., and Yoon, K. (1981), "Methods for multiple attribute decision making," Multiple attribute decision making: methods and applications a state-of-the-art survey, Vol., No., pp. 58-191.
Irfan, M., Elavarasan, R. M., Ahmad, M., Mohsin, M., Dagar, V., and Hao, Y. (2022), "Prioritizing and overcoming biomass energy barriers: Application of AHP and G-TOPSIS approaches," Technological Forecasting and Social Change, Vol. 177, No., pp. 121524.
Kagermann, H., Helbig, J., Hellinger, A., and Wahlster, W. (2013), Recommendations for implementing the strategic initiative INDUSTRIE 4.0: Securing the future of German manufacturing industry; final report of the Industrie 4.0 Working Group. Forschungsunion.
Karami, F. and Dariane, A. (2022), "A review and evaluation of multi and many-objective optimization: Methods and algorithms," Glob J Ecol, Vol. 7, No. 2, pp. 104-119.
Karatop, B., Kubat, C., and Uygun, Ö. (2015), "Talent management in manufacturing system using fuzzy logic approach," Computers & Industrial Engineering, Vol. 86, No., pp. 127-136.
Keeney, R. L. and Raiffa, H. (1993), Decisions with multiple objectives: preferences and value trade-offs. Cambridge university press.
Kikuchi, T., Nishimura, K., and Stachurski, J. (2018), "Span of control, transaction costs, and the structure of production chains," Theoretical Economics, Vol. 13, No. 2, pp. 729-760.
Ku, C.-C., Chien, C.-F., and Ma, K.-T. (2020), "Digital transformation to empower smart production for Industry 3.5 and an empirical study for textile dyeing," Computers & Industrial Engineering, Vol. 142, No., pp. 106297.
Kuhn, H. W. (1955), "The Hungarian method for the assignment problem," Naval research logistics quarterly, Vol. 2, No. 1‐2, pp. 83-97.
Larraín, S., Pradenas, L., Pulkkinen, I., and Santander, F. (2020), "Multiobjective optimization of a continuous kraft pulp digester using SPEA2," Computers & Chemical Engineering, Vol. 143, No., pp. 107086.
Lee, C.-Y. and Chien, C.-F. (2014), "Stochastic programming for vendor portfolio selection and order allocation under delivery uncertainty," Or Spectrum, Vol. 36, No., pp. 761-797.
Lee, D.-H., Lee, C.-H., Choi, S.-H., and Kim, K.-J. (2019), "A method for wafer assignment in semiconductor wafer fabrication considering both quality and productivity perspectives," Journal of Manufacturing Systems, Vol. 52, No., pp. 23-31.
Li, X., Fang, S.-C., Guo, X., Deng, Z., and Qi, J. (2016), "An extended model for project portfolio selection with project divisibility and interdependency," Journal of Systems Science and Systems Engineering, Vol. 25, No. 1, pp. 119-138.
Li, Y., Yang, F., Zhang, X., Fu’E, R., and Chen, C. (2022), "Intelligent Manufacturing Execution Design of Gear Industry Based on Internet of Things Technology," Vol., No., pp.
Lin, C.-C. and Liu, Y.-T. (2008), "Genetic algorithms for portfolio selection problems with minimum transaction lots," European Journal of Operational Research, Vol. 185, No. 1, pp. 393-404.
Lin, K.-Y., Chien, C.-F., and Kerh, R. (2016), "UNISON framework of data-driven innovation for extracting user experience of product design of wearable devices," Computers & Industrial Engineering, Vol. 99, No., pp. 487-502.
Lin, Y.-H., Chien, C.-F., and Yu, C.-M. (2015), "UNISON decision analysis framework for workforce planning for semiconductor fabs and an empirical study," International Journal of Industrial Engineering, Vol. 22, No. 5, pp.
Lin, Y.-S., Chien, C.-F., and Chou, D. (2022), "UNISON decision framework for hybrid optimization of wastewater treatment and recycle for Industry 3.5 and cleaner semiconductor manufacturing," Resources, Conservation and Recycling, Vol. 182, No., pp. 106282.
Lyu, H.-M., Zhou, W.-H., Shen, S.-L., and Zhou, A.-N. (2020), "Inundation risk assessment of metro system using AHP and TFN-AHP in Shenzhen," Sustainable Cities and Society, Vol. 56, No., pp. 102103.
Ma, G., Li, X., and Zheng, J. (2020), "Efficiency and equity in regional coal de-capacity allocation in China: a multiple objective programming model based on Gini coefficient and Data Envelopment Analysis," Resources Policy, Vol. 66, No., pp. 101621.
Maree, M., Kmail, A. B., and Belkhatir, M. (2019), "Analysis and shortcomings of e-recruitment systems: Towards a semantics-based approach addressing knowledge incompleteness and limited domain coverage," Journal of Information Science, Vol. 45, No. 6, pp. 713-735.
Mor, R. S., Bhardwaj, A., Singh, S., and Sachdeva, A. (2018), "Productivity gains through standardization-of-work in a manufacturing company," Journal of Manufacturing Technology Management, Vol., No., pp.
Nabeeh, N. A., Smarandache, F., Abdel-Basset, M., El-Ghareeb, H. A., and Aboelfetouh, A. (2019), "An integrated neutrosophic-topsis approach and its application to personnel selection: A new trend in brain processing and analysis," IEEE Access, Vol. 7, No., pp. 29734-29744.
OECD. (2023). "OECD Data: Hours worked." Retrieved 2023/8/16, from https://data.oecd.org/emp/hours-worked.htm#indicator-chart.
Oktavianti, E., Komala, N., and Nugrahani, F. (2019), "Simple multi attribute rating technique (SMART) method on employee promotions," Proceedings of Journal of Physics: Conference Series.
Pal, R., Chaudhuri, T. D., and Mukhopadhyay, S. (2021), "Portfolio formation and optimization with continuous realignment: a suggested method for choosing the best portfolio of stocks using variable length NSGA-II," Expert Systems with Applications, Vol. 186, No., pp. 115732.
Pei, M., Lin, P., Du, J., Li, X., and Chen, Z. (2021), "Vehicle dispatching in modular transit networks: A mixed-integer nonlinear programming model," Transportation Research Part E: Logistics and Transportation Review, Vol. 147, No., pp. 102240.
Pessach, D., Singer, G., Avrahami, D., Ben-Gal, H. C., Shmueli, E., and Ben-Gal, I. (2020), "Employees recruitment: A prescriptive analytics approach via machine learning and mathematical programming," Decision Support Systems, Vol. 134, No., pp. 113290.
Qin, Y., Zhang, J., Chan, F. T., Chung, S. H., Niu, B., and Qu, T. (2020), "A two-stage optimization approach for aircraft hangar maintenance planning and staff assignment problems under MRO outsourcing mode," Computers & Industrial Engineering, Vol. 146, No., pp. 106607.
R Gómez-Mejía, L., B Balkin, D., and L Cardy, R. (2012), Managing human resources, 7th. Pearson, Boston.
Rabbani, Q., Khan, A., and Quddoos, A. (2019), "Modified Hungarian method for unbalanced assignment problem with multiple jobs," Applied Mathematics and Computation, Vol. 361, No., pp. 493-498.
Rahimian, E., Akartunalı, K., and Levine, J. (2017), "A hybrid integer programming and variable neighbourhood search algorithm to solve nurse rostering problems," European Journal of Operational Research, Vol. 258, No. 2, pp. 411-423.
Reenock, C., Konisky, D. M., and Uttermark, M. J. (2022), "Chain of command vs. Who’s in command: Structure, politics, and regulatory enforcement," Policy Studies Journal, Vol. 50, No. 4, pp. 797-821.
Remenova, K., Skorkova, Z., and Jankelova, N. (2018), "Span of control in teamwork and organization structure," Montenegrin Journal of Economics, Vol. 14, No. 2, pp. 155-165.
Robbins, S. P. and Judge, T. A. (2013), Organizational behavior. Pearson, Boston.
Saaty, T. L. (2008), "Decision making with the analytic hierarchy process," International journal of services sciences, Vol. 1, No. 1, pp. 83-98.
Saiz, M., Lostumbo, M. A., Juan, A. A., and Lopez‐Lopez, D. (2022), "A clustering‐based review on project portfolio optimization methods," International Transactions in Operational Research, Vol. 29, No. 1, pp. 172-199.
Saqlain, M., Abbas, Q., and Lee, J. Y. (2020), "A deep convolutional neural network for wafer defect identification on an imbalanced dataset in semiconductor manufacturing processes," IEEE Transactions on Semiconductor Manufacturing, Vol. 33, No. 3, pp. 436-444.
Singh, J., Singh, H., and Singh, G. (2018), "Productivity improvement using lean manufacturing in manufacturing industry of Northern India: A case study," International Journal of Productivity and Performance Management, Vol., No., pp.
Smeets, V., Waldman, M., and Warzynski, F. (2019), "Performance, career dynamics, and span of control," Journal of Labor Economics, Vol. 37, No. 4, pp. 1183-1213.
Solow, R. M. (1957), "Technical change and the aggregate production function," The review of Economics and Statistics, Vol., No., pp. 312-320.
Tavana, M., Khanjani Shiraz, R., and Di Caprio, D. (2019), "A chance-constrained portfolio selection model with random-rough variables," Neural Computing and Applications, Vol. 31, No. 2, pp. 931-945.
Teece, D. J. (2018), "Business models and dynamic capabilities," Long range planning, Vol. 51, No. 1, pp. 40-49.
Trojanowska, J., Kolinski, A., Galusik, D., Varela, M. L., and Machado, J. (2018), "A methodology of improvement of manufacturing productivity through increasing operational efficiency of the production process," in: (eds.), Advances in Manufacturing, Springer, pp. 23-32.
Tzeng, G.-H. and Huang, J.-J. (2011), Multiple attribute decision making: methods and applications. CRC press, Boca Raton.
Ugoani, J. (2021), "Understanding the Relationship Between Departmentalization and Management Performance: First Bank’s Exemplary Model," International Journal of Environmental Planning and Management, Vol. 7, No. 2, pp. 59-71.
Valouxis, C., Gogos, C., Goulas, G., Alefragis, P., and Housos, E. (2012), "A systematic two phase approach for the nurse rostering problem," European Journal of Operational Research, Vol. 219, No. 2, pp. 425-433.
Van den Bergh, J., Beliën, J., De Bruecker, P., Demeulemeester, E., and De Boeck, L. (2013), "Personnel scheduling: A literature review," European journal of operational research, Vol. 226, No. 3, pp. 367-385.
Verma, S., Pant, M., and Snasel, V. (2021), "A comprehensive review on NSGA-II for multi-objective combinatorial optimization problems," Ieee Access, Vol. 9, No., pp. 57757-57791.
Whiting, K. (2020), "These are the top 10 job skills of tomorrow–and how long it takes to learn them," Proceedings of World Economic Forum.
Wu, M.-C. and Sun, S.-H. (2006), "A project scheduling and staff assignment model considering learning effect," The International Journal of Advanced Manufacturing Technology, Vol. 28, No. 11, pp. 1190-1195.
Wu, Y., Xu, C., Ke, Y., Chen, K., and Sun, X. (2018), "An intuitionistic fuzzy multi-criteria framework for large-scale rooftop PV project portfolio selection: Case study in Zhejiang, China," Energy, Vol. 143, No., pp. 295-309.
Xiong, J., Wang, R., Kou, G., and Xu, L. (2021), "Solving periodic investment portfolio selection problems by a data-assisted multiobjective evolutionary approach," IEEE Transactions on Cybernetics, Vol. 52, No. 11, pp. 11418-11430.
Xu, S., Stienmetz, J., and Ashton, M. (2020), "How will service robots redefine leadership in hotel management? A Delphi approach," International Journal of Contemporary Hospitality Management, Vol. 32, No. 6, pp. 2217-2237.
Zhao, Y., Hryniewicki, M. K., Cheng, F., Fu, B., and Zhu, X. (2018), "Employee turnover prediction with machine learning: A reliable approach," Proceedings of Proceedings of SAI intelligent systems conference.
Zitzler, E., Laumanns, M., and Thiele, L. (2001), "SPEA2: Improving the strength Pareto evolutionary algorithm," TIK-report, Vol. 103, No., pp.
中華民國主計總處. (2023). "中華民國統計資訊網主計總處薪資及生產力統計." Retrieved 2023/6/28, from https://www.stat.gov.tw/cl.aspx?n=2712.
中華民國國家發展委員會. (2023). "人口推估查詢系統." Retrieved 2023/08/16, from https://pop-proj.ndc.gov.tw/dataSearch5.aspx?uid=3109&pid=59.
中華民國勞動部. (2023). "勞動統計查詢網年總工時." Retrieved 2023/8/16, from https://statfy.mol.gov.tw/index17.aspx.
簡禎富 (2019), 工業3.5台灣企業邁向智慧製造與數位決策的戰略. 天下雜誌, 台北市.
簡禎富, 游智閔, and 徐紹鐘 (2009), "紫式決策分析以建構半導體晶圓廠人力規劃決策模型," 管理與系統, Vol. 16, No. 2, pp. 157-180.