1.李維平王雅賢、江正文(2008)。「粒子群最佳化演算法改良之研究」。工程與技術學刊,第4卷,第2期,頁51–62。
2.李浩均(2016)。應用人工智慧演算法於人數限制及固定參觀時間之博物館路徑問題,國立虎尾科技大學工業工程與管理研究所,碩士論文。3.沈峻緯(2018)。應用人工智慧演算法於多處理器最佳化工作排程問題之研究,國立虎尾科技大學工業工程與管理研究所,碩士論文。4.林李旺(2013)。突破品質水準-實驗設計與田口方法之實際應用,臺北市:全華圖書股份有限公司。
5.林豐澤(2005),「演化式計算上篇:演化式演算法的三種理論模式」,智慧科技與應用統計學報,第3卷,第1期,頁1–28。
6.林豐澤(2005),「演化式計算下篇:演化式演算法的三種理論模式」,智慧科技與應用統計學報,第3卷,第1期,頁29–56。
7.邱顯明、謝復恩(2012)。以免疫演算法探討廢輪胎處理場區位指派與運送路線選擇之研究,淡江大學運輸管理學系,會議論文。
8.涂榮城(2017)。應用人工智慧演算法於多選擇性及固定參觀時間之博物館路徑問題,國立虎尾科技大學工業工程與管理研究所,碩士論文。9.陳佳順(2014)。人工智慧演算法於博物館路徑的應用,國立虎尾科技大學工業工程與管理研究所,碩士論文。10.陳惠美(1992)。「觀眾的引導及參觀動線問題的探討」,博物館學季刊,頁83–90。
11.許正良(2013)。應用人工智慧法於居家照顧服務排程路徑規劃問題,國立虎尾科技大學工業管理系工業工程與管理碩士班,碩士論文。12.國史館台灣文獻館,https://www.th.gov.tw/
13.程秉逢(2015)。應用人工智慧演算法探討健康檢查之排程問題,國立虎尾科技大學工業管理系工業工程與管理碩士班,碩士論文。14.黃柏輔(2010)。利用多重軌跡搜尋演算法解決開放式工廠排程問題,國立中興大學資訊網路多媒體碩士班,碩士論文。15.黃建銘(2014)。演化式演算法於開放型固定間隔參觀時間之遊客導覽排程問題,國立虎尾科技大學工業工程與管理研究所,碩士論文。16.黃士滔、郭珀菁(2014)。「田口方法在拉球測試參數最佳化的應用」,管理資訊計算,3,頁428–438。
17.廖國清(2005)。最佳演算法應用於負載預測及機組排程問題,國立臺北科技大學自動化科技研究所,博士論文。18.蔡宗佑(2015)。應用人工智慧演算法於新的博物館路徑問題之探討,國立虎尾科技大學工業工程與管理研究所,碩士論文。19.鄧宗倫(2010)。應用人工智慧法於最佳消毒作業之時窗限制車輛途程問題,國立虎尾科技大學工業管理系工業工程與管理碩士班,碩士論文。20.蔡聿威(2015)。整合DEMATEL 與田口方法於精實六標準差之應用模式,中原大學工業與系統工程研究所,碩士論文。21.蘇桂成(2014)。應用人工智慧演算法探討需多種工序的多工件開放式排程問題,國立虎尾科技大學工業工程與管理研究所,碩士論文。22.蘇朝墩(2013)。品質工程,臺北市:三民書局。
23.Anand, E. & Panneerselvam, R. (2016). “A Study of Crossover Operators for Genetic Algorithm and Proposal of a New CrossoverOperator to Solve Open Shop Scheduling Problem”, American Journal of Industrial and Business Management, Vol 6, 774–789.
24.Armano, G. & Farmani, M.R. (2016). “Multiobjective clustering analysis using particle swarm optimization”, Expert Systems With Applications, Vol 55, 184–193.
25.Bai, D., Zhang, Z., Zhang, Q. & Tang, M. (2016). “Open shop scheduling problem to minimize total weighted completion time”, Engineering Optimization, Vol 49, 98–112.
26.Brucker, P., Hurink, J., Jurisch, B. & Wgstmann, B. (1997). “A branch & bound algorithm for the open-shop problem”, Discrete Applied Mathematics, Vol 76, 43–59.
27.Chou, S.Y. & Lin, S.W. (2007). “Museum visitor routing problem with the balancing of concurrent visitors”, Proceedings of 14th ISPE International Conference on Concurrent Engineering:Research and Applications, Sao Jose dos Campos, SP, Brazil, 345–353.
28.Eberhart, R. & Kennedy, J. (1995). “A new optimizer using particle swarm theory. In Micro Machine and Human Science”, Proceedings of the Sixth International Symposium, 39–43. IEEE.
29.Ghareb, A.S., Bakar, A.A. & Hamdan, A.R. (2016). “Hybrid feature selection based on enhanced genetic algorithm for text categorization”, Expert Systems With Applications, Vol 49, 31–47.
30.Goldberg, D.E. & Holland, J. (1989). “Genetic Algorithms in Search, Optimization and Machine Learning, Machine Learning”, Vol 3, 95–99.
31.Golpayegani, M., Fathali, J. & Moradi, H. (2017). “A particle swarm optimization method for semi-obnoxious line locationproblem with rectilinear norm”, Computers & Industrial Engineering, Vol 109, 71–78.
32.Holland, J. (1975). “An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence”, Adaptation in Natural and Artificial Systems.
33.Huang, S.H. & Lin, T.H. (2014). “Using Ant Colony Optimization to solve Periodic Arc Routing Problem with Refill Points”, Journal of Industrial and Production Engineering, Vol 31, No. 7, 441–451.
34.Hulett, M., Damodaran, P. & Amouie, M. (2017). “Scheduling non-identical parallel batch processing machines to minimizetotal weighted tardiness using particle swarm optimization”, Computers & Industrial Engineering, Vol 113, 425–436.
35.Huang, S.J. (1999). “Enhancement of thermal unit commitment using immune algorithms based optimization approaches”, Electrical Power and Energy Systems, Vol 21, 245–252.
36.Kozeny, V. (2015). “Genetic algorithms for credit scoring: Alternative fitness function performance comparison”, Expert Systems with Applications, Vol 42, 2998–3004.
37.Lalla-Ruiz, E., Shi, X. & Voß, S. (2018). “The waterway ship scheduling problem”, Transportation Research Part D, Vol 60, 191–209.
38.Lee, Y. & Lee, J. (2015). “Binary tree optimization using genetic algorithm for multiclass supportvector machine”, Expert Systems with Applications, Vol 42, 3843–3851.
39.Lenstra, J.K. , & Kan, A.H.G. (1976). “On General Routing Problem, Networks”, Vol 6, 273–280.
40.Liaw, C.F. (2000). “A hybrid genetic algorithm for the open shop scheduling problem”, European Journal of Operational Research, Vol 124, 28–42.
41.Min, D. & Yih, Y. (2010). “An elective surgery scheduling problem considering patient priority”, Computers & OperationsResearch, Vol 37, 1091–1099.
42.Mallawaarachchi, V. (2017). Introduction to Genetic Algorithms - Including Example Code. https://towardsdatascience.com/
43.Shao, X., Chen, Z. & Lin, X. (2000). “Resolution of multicomponent overlapping chromatogram usingan immune algorithm and genetic algorithm”, Chemometrics and Intelligent Laboratory Systems, Vol 50, 91-99.
44.Tsai, C.Y. & Kao, I.W. (2011). “Particle swarm optimization with selective particle regeneration for data clustering”, Expert Systems with Applications, Vol 38, 6, 6565–6576.
45.Thierens, D. & Goldber, D. (1994). “Convergence Models of Genetic Algorithm Selection Schemes”.
46.Yu, V.F., Lin, S.W. & Chou, S.Y. (2010). “The museum visitor routing problem”, Applied Mathematics and Computation, Vol 216, 719–729