中文部分
1.羅中育(2001)。田口品質工程應用於模擬退火法參數組合-以呂瀅推銷員問題(TSP)為例。未出版之碩士論文,國立雲林科技大學,雲林縣。2.盧研伯(2003)。混合式模擬退火法應用於具迴流特性流程工廠之研究。未出版之碩士論文,國立台北科技大學,台北市。3.李宜原(2004)。改良式遺傳演算法於零工式生產排程系統之應用。未出版之碩士論文,國立臺灣海洋大學,基隆市。4.柯惠雯(2001)。結合模擬退火法與禁忌搜尋法在流程式生產排程之應用。未出版之碩士論文,大葉大學,彰化縣。5.何惠雯(2001)。具等候時間窗口限制之零工式生產排程工作順序之決定。未出版之碩士論文,國立中央大學,桃園縣。6.黃俊龍(2004)。應用模擬退火法規劃具有加工順序限制之非相關平行機台多目標排程。未出版之碩士論文,國立屏東科技大學,屏東縣。7.周德華(2001)。多目標迴流環境下之限制驅導式排程系統。未出版之碩士論文,國立中央大學,桃園縣。8.張皇文(2006)。液晶顯示器陣列製程之彈性零工式生產排程。未出版之碩士論文,國立清華大學,新竹市。9.陳建良(1995)。排程概述。機械工業雜誌,153,122-137。10.程偉哲(2010)。時窗限制之彈性零工式生產排程研究-以二費洛蒙蟻群演算法求解。未出版之碩士論文,天主教輔仁大學,新北市。11.曾偉杰(2011)。以模擬退火法求解流線型製造單元排程。未出版之碩士論文,國立交通大學,新竹市。12.游麗萍(2004)。應用蟻族最佳化規劃有倉儲限制的生產排程。未出版之碩士論文,國立屏東科技大學,屏東縣。13.吳貴彬(1998)。以模擬退火法求解工單式生產系統之排程問題--最小化總延遲時間。未出版之碩士論文,國立成功大學,台南市。14.魏文鍇(2003)。利用啟發式演算法求解工單式生產系統排程中時窗限制與釋放時間限制問題。未出版之碩士論文,國立成功大學,台南市。15.吳秉威(2005)。以遺傳演算法求解PCB廠生產排程問題。未出版之碩士論文,南台科技大學,台南市。英文部分
1.Chen, J., Pan, P., & Lin, C. (2006). A hybrid genetic algorithm for the re-entrant flow-shop scheduling problem. Expert Systems with Applications, 34(1), 570-577.
2.Garey, M.R., Johnson, D.S., & Sethi, R. (1976). The complexity of flowshop and job shop scheduling. Mathematics of Operations Research, 1(2), 117-129
3.Haupt, R. (1989). A survey of priority rule-based scheduling. Operations-Research-Spektrum, 11(1), 3-16.
4.Kaihara, T., Fujii, N., Tsujibe, A., & Nonaka, Y. (2010) Proactive maintenance scheduling in a re-entrant flow shop using Lagrangian decomposition coordination method. CIRP Annals-Manufacturing Technology, 59(1), 453-456.
5.Lenstra, J.K., & Rinnooy Kan, A.H.G. (1979). Computational complexity of discrete optimization problem. Annals of Discrete Mathematics, 4, 121-140.
6.Lin, D., Lee, C., & Ho, W. (2013). Multi-level genetic algorithm for the resource-constrained re-entrant scheduling problem in the flow shop. Engineering Applications of Artificial Intelligence, 26(4), 1282–1290.
7.Mahfoud, S.W., & Goldberg, D.E. (1995). Parallel recombinative simulated annealing: A genetic algorithm. Parallel Computing, 21(1), 1-28.
8.Mattfeld, D.C. & Vaessens, R.J.M. (2003). Job shop problem test instances set. Available: OR Library online, <http://people.brunel.ac.uk/~mastjjb/jeb/orlib/jobshopinfo.html>
9.Ohta, H., & Nakatani, H. (2006). A heuristic job-shop scheduling algorithm to minimize the total holding cost of completed and in-process products subject to no tardy jobs. International Journal of Production Economics, 101(1), 19-29.
10.Parthanadee, P., & Buddhakulsomsiri, J. (2010). Simulation modeling and analysis for production scheduling using real-time dispatching rules: A case study in canned fruit industry. Computers and Electronics in Agriculture, 70(1), 245-255.
11.Raaymakers, W.H.M., & Hoogeveen, J.A. (2000). Scheduling multipurpose batch process industries with no-wait restrictions by simulated annealing. European Journal of Operational Research, 126(1), 131-151.
12.Saraiva, J., Pereira, M., Mendes, V., & Sousa, J. (2011). A Simulated Annealing based approach to solve the generator maintenance scheduling problem. Electric Power Systems Research, 81(7), 1283–1291.
13.Satake. T., Morikawa, K., Takahashi, K., & Nakamura, N. (1999). Simulated annealing approach for minimizing the makespan of the general job-shop. International Journal of Production Economics, 60-61, 515-522.
14.Wiendahl, H.-P., & Scholtissek, P. (1994). Management and control of complexity in manufacturing. CIRP Annals - Manufacturing Technology, 43(2), 533-540.
15.Wu, C.-C., Hsu, P.-H., & Lai, K. (2011). Simulated-annealing heuristics for the single-machine scheduling problem with learning and unequal job release times. Journal of Manufacturing Systems, 30(1), 54–62.
16.Zhang, R., Song, S., & Wu, C. (2013). A hybrid artificial bee colony algorithm for the job shop scheduling problem. International Journal of Production Economics, 141(1), 167–178.
17.Zhou, H., Feng, Y., & Han, L. (2001). The hybrid heuristic genetic algorithm for job shop scheduling. Computers & Industrial Engineering, 40(3), 191-200.