How to cite this paper
Djatna, T & Amien, G. (2020). Bi-objective freight scheduling optimization in an integrated forward/reverse logistic network using non-dominated sorting genetic algorithm-II.Decision Science Letters , 9(1), 91-106.
Refrences
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Barwaldt, M., Franzin, R., Casarin, V., dos Santos, A. (2014). Using the theory of graphs on the implementation of bike lane in small towns, in: Procedia of Social and Behavioral Sciences. Presented at the XVIII Congreso Panamericano de Ingeniería de Tránsito, Transporte y Logística, Elsevier, Santander (ES), pp. 350–358.
Baumik, P.K. (2015). Supply chain network design based on integration of forward and reverse logistics. Global Business Review, 16(4), pp. 680-699.
Cataruzza, D., Absi, N., Feillet, D., Vidal, T. (2013). A memetic algorithm for the multi trip vehicle routing problem. European Journal of Operational Research, 236, 833–848.
de Brito, M., Dekker, R. (2003). A framework for reverse logistics (ERIM Report), Research in Management. Erasmus Research Institute Of Management, Rotterdam (NL).
de Oliveira, L. S. D., & Saramago, S. F. (2010). Multiobjective optimization techniques applied to engineering problems. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 32(1), 94-105.
Deb, K., & Agrawal, R.B. (1994). Simulated binary crossover for continuous search space (Technical Report No. IITK/ME/SMD-94027). Indian Institute of Technology, Kanpur.
Deb, K., Goyal, M. (1996). A combined genetic adaptive search (GeneAS) for engineering design. Computer Science and Informatics, 26, 30–45.
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6, 182–197.
Démare, T., Bertelle, C., Dutot, A., Lévêque, L. (2017). Modeling logistic systems with an agent-based model and dynamic graphs. Journal of Transport Geography, 62, 51–65.
Diestel, R. (2005). Graph Theory. Springer, New York (US).
Dondo, R.G., Mendez, C.A. (2016). Operational planning of forward and reverse logistic activities on multi-echelon supply-chain networks. Computers and Chemical Engineering, 88, 170–184.
Fazlollahtabar, H. (2018). Reverse supply chain vehicle routing problem: similarity pattern model in Supply chain management models : forward, reverse, uncertain, and intelligent foundations with case studies book, pp. 217-225.
Fleischmann, M., Beullens, P., BLOEMHOF‐RUWAARD, J. M., & Van Wassenhove, L. N. (2001). The impact of product recovery on logistics network design. Production and Operations Management, 10(2), 156-173.
Gudehus, T., Kotzab, H. (2009). Comprehensive Logistic. Springer, Berlin (DE).
Guidice, F. (2013). Graph-based approach for modeling, simulation, and optimization of life cycle resource flows. Reverse Supply Chain book, ed, Gupta, S.M. CRC Press.
Hadka, D. (2011). Beginner’s Guide to the MOEA Framework.
Hadka D. (2017). MOEA Framework version 2.12. Available at: https://github.com/MOEAFramework/MOEAFramework/releases/download/v2.12/MOEAFramework-2.12-Source.tar.gz
Kacprzyk, J., & Pedrycz, W. (Eds.). (2015). Springer Handbook of Computational Intelligence. Springer, Berlin (DE).
Khajavi, L.T., Seyed-Hosseini, S.M., Makui, A. (2011). An integrated forward/reverse logistics network optimization model for multi-stage capacitated supply chain. Scientific Research, 3, 229–235.
Lee, D.H., & Dong, M. (2008). A heuristic approach to logistics network design for end-of-lease computer products recovery. Transportation Research Part E, 44, 455–474.
Likaj, R., Shala, A., Mehmetaj, M., Hyseni, P., Bajrami, X. (2013). Application of graph theory to find optimal paths for the transportation problem. Presented at the 15th Workshop on International Stability, Technology, and Culture, The International Federation of Automatic Contro, Prishtina (KO).
Parkhi, S., Jagadeesh, D., Kumar, R.A. (2014). A study on transportation cost optimization in retail distribution. Journal of Supply Chain Management System, 3, 31–38.
Pishvaee, M.S., Jolai, F., Razmi, J. (2009). A stochastic optimization model for integrated forward/reverse logistics network design. Journal of Manufacturing System, 28, 107–114.
Price, E., & Ostfeld, A. (2014). Optimal Water System Operation Using Graph Theory Algorithms, in: Procedia Engineering. Presented at the 16th Conference on Water Distribution System Analysis, Elsevier, pp. 502–208.
Rao, R., & Savsani, V. (2012). Mechanical Design Optimization Using Advanced Optimization Techniques. Springer, Berlin (DE).
Rogers, D., & Tibben-Lembke, R. (1999). Going Backwards: Reverse Logistics Trends and Practices. Pittsburgh (PA). Reverse Logistics Executive Council, Pittsburgh (PA).
Siregar, H.H. (2012). Solving Vehicle Routing Problem on the Distributions of Highland Vegetables Using Genetic Algorithm (Case study PT Saung Mirwan) (Undergraduate Thesis). Bogor Agricultural University, Bogor (ID).
Tseng, Y., Yue, W.L., Taylor, M.A.P. (2005). The role of transportation in logistics chain, in: Proceedings of the Eastern Asia Society for Transportation Studies. Presented at the The 6th EASTS conference, Bangkok (TH), pp. 1657–1672.
Zaki, S.A., Mousa, A.A.A., Geneedi, H.M., Elmekawy, A.Y. (2012). Efficient multiobjective genetic algorithm for solving transportation, assignment, and transshipment problems. Applied Mathematics, 3, 92–99.
[Oracle]. 2017. MySQL Community Edition version 5.7.18. Available at: https://dev.mysql.com/downloads/mysql/
Barwaldt, M., Franzin, R., Casarin, V., dos Santos, A. (2014). Using the theory of graphs on the implementation of bike lane in small towns, in: Procedia of Social and Behavioral Sciences. Presented at the XVIII Congreso Panamericano de Ingeniería de Tránsito, Transporte y Logística, Elsevier, Santander (ES), pp. 350–358.
Baumik, P.K. (2015). Supply chain network design based on integration of forward and reverse logistics. Global Business Review, 16(4), pp. 680-699.
Cataruzza, D., Absi, N., Feillet, D., Vidal, T. (2013). A memetic algorithm for the multi trip vehicle routing problem. European Journal of Operational Research, 236, 833–848.
de Brito, M., Dekker, R. (2003). A framework for reverse logistics (ERIM Report), Research in Management. Erasmus Research Institute Of Management, Rotterdam (NL).
de Oliveira, L. S. D., & Saramago, S. F. (2010). Multiobjective optimization techniques applied to engineering problems. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 32(1), 94-105.
Deb, K., & Agrawal, R.B. (1994). Simulated binary crossover for continuous search space (Technical Report No. IITK/ME/SMD-94027). Indian Institute of Technology, Kanpur.
Deb, K., Goyal, M. (1996). A combined genetic adaptive search (GeneAS) for engineering design. Computer Science and Informatics, 26, 30–45.
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6, 182–197.
Démare, T., Bertelle, C., Dutot, A., Lévêque, L. (2017). Modeling logistic systems with an agent-based model and dynamic graphs. Journal of Transport Geography, 62, 51–65.
Diestel, R. (2005). Graph Theory. Springer, New York (US).
Dondo, R.G., Mendez, C.A. (2016). Operational planning of forward and reverse logistic activities on multi-echelon supply-chain networks. Computers and Chemical Engineering, 88, 170–184.
Fazlollahtabar, H. (2018). Reverse supply chain vehicle routing problem: similarity pattern model in Supply chain management models : forward, reverse, uncertain, and intelligent foundations with case studies book, pp. 217-225.
Fleischmann, M., Beullens, P., BLOEMHOF‐RUWAARD, J. M., & Van Wassenhove, L. N. (2001). The impact of product recovery on logistics network design. Production and Operations Management, 10(2), 156-173.
Gudehus, T., Kotzab, H. (2009). Comprehensive Logistic. Springer, Berlin (DE).
Guidice, F. (2013). Graph-based approach for modeling, simulation, and optimization of life cycle resource flows. Reverse Supply Chain book, ed, Gupta, S.M. CRC Press.
Hadka, D. (2011). Beginner’s Guide to the MOEA Framework.
Hadka D. (2017). MOEA Framework version 2.12. Available at: https://github.com/MOEAFramework/MOEAFramework/releases/download/v2.12/MOEAFramework-2.12-Source.tar.gz
Kacprzyk, J., & Pedrycz, W. (Eds.). (2015). Springer Handbook of Computational Intelligence. Springer, Berlin (DE).
Khajavi, L.T., Seyed-Hosseini, S.M., Makui, A. (2011). An integrated forward/reverse logistics network optimization model for multi-stage capacitated supply chain. Scientific Research, 3, 229–235.
Lee, D.H., & Dong, M. (2008). A heuristic approach to logistics network design for end-of-lease computer products recovery. Transportation Research Part E, 44, 455–474.
Likaj, R., Shala, A., Mehmetaj, M., Hyseni, P., Bajrami, X. (2013). Application of graph theory to find optimal paths for the transportation problem. Presented at the 15th Workshop on International Stability, Technology, and Culture, The International Federation of Automatic Contro, Prishtina (KO).
Parkhi, S., Jagadeesh, D., Kumar, R.A. (2014). A study on transportation cost optimization in retail distribution. Journal of Supply Chain Management System, 3, 31–38.
Pishvaee, M.S., Jolai, F., Razmi, J. (2009). A stochastic optimization model for integrated forward/reverse logistics network design. Journal of Manufacturing System, 28, 107–114.
Price, E., & Ostfeld, A. (2014). Optimal Water System Operation Using Graph Theory Algorithms, in: Procedia Engineering. Presented at the 16th Conference on Water Distribution System Analysis, Elsevier, pp. 502–208.
Rao, R., & Savsani, V. (2012). Mechanical Design Optimization Using Advanced Optimization Techniques. Springer, Berlin (DE).
Rogers, D., & Tibben-Lembke, R. (1999). Going Backwards: Reverse Logistics Trends and Practices. Pittsburgh (PA). Reverse Logistics Executive Council, Pittsburgh (PA).
Siregar, H.H. (2012). Solving Vehicle Routing Problem on the Distributions of Highland Vegetables Using Genetic Algorithm (Case study PT Saung Mirwan) (Undergraduate Thesis). Bogor Agricultural University, Bogor (ID).
Tseng, Y., Yue, W.L., Taylor, M.A.P. (2005). The role of transportation in logistics chain, in: Proceedings of the Eastern Asia Society for Transportation Studies. Presented at the The 6th EASTS conference, Bangkok (TH), pp. 1657–1672.
Zaki, S.A., Mousa, A.A.A., Geneedi, H.M., Elmekawy, A.Y. (2012). Efficient multiobjective genetic algorithm for solving transportation, assignment, and transshipment problems. Applied Mathematics, 3, 92–99.
[Oracle]. 2017. MySQL Community Edition version 5.7.18. Available at: https://dev.mysql.com/downloads/mysql/