[1] Shen, W.D.H. (1999). Norrie, Agent-based systems for intelligent manufacturing: A state-of-the-art survey, International Journal Knowledge and Information Systems, 1(2): 129–156.
[2] Dhaenens-Flipo, G., Finke, G. (2001). An integrated model for an industrial production-distribution problem, IIE Transactions, 33(9): 705–715.
[3] Soares, A.L., Azevedo, A.L., De Sousa, J.P. (2000). Distributed planning and control systems for thevirtual enterprise: Organizational requirementsand development life-cycle, Journal of Intelligent Manufacturing, 11: 253-270.
[4] بشیری، مهدی، شرافتی، مهتاب (1392). طراحی دو هدفه شبکه زنجیره تأمین حلقه بسته با در نظر گرفتن معیارهای همبسته در محیط فازی، نشریه پژوهشهای مهندسی صنایع در سیستمهای تولید، شماره 1، صفحه 25-36.
[5] Williams, J.F. (1981). Heuristic techniques for simultaneous scheduling of production and distribution in multi-echelon structures: Theory and empirical comparisons, Management Science, 27: 336-352.
[6] Blumenfeld, D.E., Burns, L.D., Daganzo, C.F., Frick, M.C., Hall, R.W. (1987) Reducing logistics cost at General Motors, Interfaces, 17: 26-47.
[7] Sambasivan, M., Yahya, S. (2005). A Lagrangean-based heuristic for multi-plant, multi-item, multi-period capacitated lot-sizing problems with inter-plant transfers, Computers & Operations Research, 32: 537-555.
[8] Pirkul, H., Jayaraman, V. (1998). A multi-commodity, multi-plant, capacitated facility location problem: Formulation and efficient heuristic solution, Computers & Operation Research, 25(10): 869-878.
[9] Kim, Y., Yun, C., Park, S.B., Park, S., Fan, L.T. (2008). An integrated model of supply network and production planning for multiple fuel products of multi-site refineries, Computers & Chemical Engineering, 32: 2529–2535.
[10] Zhang, M.T., Niu, S., Mai, M., Li, Q. (2005). Multi-factory optimization enables kit reconfiguration in semiconductor manufacturing, In Proceedings of the International Conference on Automation Science and Engineering Edmonton, Canada, 105 –112.
[11] Vincent, A.C., Stephen, F.S. (2004). Wasp-like agents for distributed factory coordination, Autonomous Agents and Multi-Agent Systems, 8: 237–266.
[12] Barroso, A.M., Torreao, J.R.A., Leite, J.C.B., Loques, O.G., Fraga, J.S. (1997). A new technique for task allocation in real-time distributed systems, InProceedings of the 7th Brazilian Symposium of Fault Tolerant Computers, Campina Grande, Brazil, 269–278.
[13] Behdani, B., Lukszo, Z., Adhitya, A., Srinivasan, R. (2010). Decentralized vs. centralized management of abnormal situations in a multi-plant enterprise using an agent-based approach,
Computer Aided Chemical Engineering,
28:1219-1224.
[14] بهنامیان، جواد، فاطمی قمی، سیدمحمدتقی (1392). ارائه الگوریتم ترکیبی بر پایه بهینه سازی گروه ذرات و روش هایپرهیوریستیک برای زمانبندی کارخانه های توزیعشده با اتحاد مجازی، نشریه پژوهشهای مهندسی صنایع در سیستمهای تولید، شماره 1، صفحه 1-11.
[15] Naderi, B., Ruiz, R. (2010). The distributed permutation flowshop scheduling problem, Computers & Operations Research, 37: 754-768.
[17] Behnamian, J., Fatemi Ghomi, S.M.T. (2014). A survey of multi-factory scheduling, Journal of Intelligent Manufacturing, 27(1), 231-249.
[18] Sule, D.R. (1997). Industrial Scheduling, 1nd ed., Boston: PWS Publishing Company.
[19] Behnamian, J. (2014). Decomposition based hybrid VNS–TS algorithm for distributed parallel factories scheduling with virtual corporation, Computers & Operations Research, 52: 181-191.
[20] Behnamian, J., Fatemi Ghomi, S.M.T. (2014). Realistic variant of just-in-time flowshop scheduling: Integration of Lp-metric method in PSO-like algorithm, The International Journal of Advanced Manufacturing Technology, 75 (9-12): 1787-1797.
[21] Brucker, P. (2007). Scheduling Algorithms, 5nd ed., New York: Springer.
[22] Zadeh, L. (1963). Optimality and non-scalar-valued performance criteria, IEEE Transactions on Automatic Control, 8: 59–60.
[23] Chankong, V., Haimes, Y.Y. (1983). Multiobjective Decision Making: Theory and Methodology, 1nd ed., New York: Elsevier Science.
[24] Behnamian, J., Fatemi Ghomi, S.M.T., Zandieh, A.M. (2009). multi-phase covering Pareto-optimal front method to multi-objective scheduling in a realistic hybrid flowshop using a hybrid metaheuristic, Expert Systems with Applications, 36: 11057-11069.
[25] Behnamian, J., Fatemi Ghomi, S.M.T. (2014). Multi-objective fuzzy multiprocessor flowshop scheduling, Applied soft computing, 21: 139–148.
[26] Talbi E.G. (2009). Metaheuristics: From Design to Implementation,John Wiley & Sons, Page 49.