How to cite this paper
Wichapa, N & Khokhajaikiat, P. (2018). Solving a multi-objective location routing problem for infectious waste disposal using hybrid goal programming and hybrid genetic algorithm.International Journal of Industrial Engineering Computations , 9(1), 75-98.
Refrences
Ahmadizar, F., Zeynivand, M., & Arkat, J. (2015). Two-level vehicle routing with cross-docking in a three-echelon supply chain: A genetic algorithm approach. Applied Mathematical Modelling, 39(22), 7065-7081.
Alumur, S., & Kara, B. Y. (2007). A new model for the hazardous waste location-routing problem. Computers & Operations Research, 34(5), 1406-1423.
Badri, M. A. (1999). Combining the analytic hierarchy process and goal programming for global facility location-allocation problem. International Journal of Production Economics, 62(3), 237-248.
Baker, B. M., & Ayechew, M. A. (2003). A genetic algorithm for the vehicle routing problem. Computers & Operations Research, 30(5), 787-800.
Birim, Ş. (2016). Vehicle Routing Problem with Cross Docking: A Simulated Annealing Approach. Procedia-Social and Behavioral Sciences, 235, 149-158.
Brandão, J. (2009). A deterministic tabu search algorithm for the fleet size and mix vehicle routing problem. European Journal of Operational Research, 195(3), 716-728.
Brandão, J. (2011). A tabu search algorithm for the heterogeneous fixed fleet vehicle routing problem. Computers & Operations Research, 38(1), 140-151.
Brandão de Oliveira, H. C., & Vasconcelos, G. C. (2010). A hybrid search method for the vehicle routing problem with time windows. Annals of Operations Research, 180(1), 125-144.
Choudhary, D., & Shankar, R. (2012). An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India. Energy, 42(1), 510-521.
Clarke, G., & Wright, J. W. (1964). Scheduling of vehicles from a central depot to a number of delivery points. Operations Research, 12(4), 568-581.
Correa, E. S., Steiner, M. T. A., Freitas, A. A., & Carnieri, C. (2001, July). A genetic algorithm for the p-median problem. In Proceedings of the 3rd Annual Conference on Genetic and Evolutionary Computation (pp. 1268-1275). Morgan Kaufmann Publishers Inc.
Dantrakul, S., Likasiri, C., & Pongvuthithum, R. (2014). Applied p-median and p-center algorithms for facility location problems. Expert Systems with Applications, 41(8), 3596-3604.
Dantzig, G. B., & Ramser, J. H. (1959). The truck dispatching problem. Management Science, 6(1), 80-91.
Dong, Q., & Cooper, O. (2016). A peer-to-peer dynamic adaptive consensus reaching model for the group AHP decision making. European Journal of Operational Research, 250(2), 521-530.
Etemadnia, H., Goetz, S. J., Canning, P., & Tavallali, M. S. (2015). Optimal wholesale facilities location within the fruit and vegetables supply chain with bimodal transportation options: An LP-MIP heuristic approach. European Journal of Operational Research, 244(2), 648-661.
Farahani, R. Z., SteadieSeifi, M., & Asgari, N. (2010). Multiple criteria facility location problems: A survey. Applied Mathematical Modelling, 34(7), 1689-1709.
Golmohammadi, A., Bani-Asadi, H., Zanjani, H., & Tikani, H. (2016). A genetic algorithm for preemptive scheduling of a single machine. International Journal of Industrial Engineering Computations, 7(4), 607-614.
Guastaroba, G., & Speranza, M. G. (2014). A heuristic for BILP problems: the single source capacitated facility location problem. European Journal of Operational Research, 238(2), 438-450.
Guo, P., Cheng, W., & Wang, Y. (2017). Hybrid evolutionary algorithm with extreme machine learning fitness function evaluation for two-stage capacitated facility location problems. Expert Systems with Applications, 71, 57-68.
Hanine, M., Boutkhoum, O., Tikniouine, A., & Agouti, T. (2016). Comparison of fuzzy AHP and fuzzy TODIM methods for landfill location selection. SpringerPlus, 5(1), 501.
Hansakul, A., Pitaksanurat, S., Srisatit, T., & Surit, P. (2010). Infectious waste management in the government hospitals by private transport sector: Case study of hospitals in the north east of Thailand. Journal of Environmental Research And Development, 4(4), 1070-1077.
Ho, W. (2007, October). Combining analytic hierarchy process and goal programming for logistics distribution network design. In Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on (pp. 714-719). IEEE.
He, T., Ho, W., Lee Ka Man, C., & Xu, X. (2012). A fuzzy AHP based integer linear programming model for the multi-criteria transshipment problem. The International Journal of Logistics Management, 23(1), 159-179.
Ho, W., Ho, G. T., Ji, P., & Lau, H. C. (2008). A hybrid genetic algorithm for the multi-depot vehicle routing problem. Engineering Applications of Artificial Intelligence, 21(4), 548-557.
Ho, W., Lee, C. K. M., & Ho, G. T. S. (2008). Optimization of the facility location-allocation problem in a customer-driven supply chain. Operations Management Research, 1(1), 69-79.
Holland, J. H. (1992). Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. MIT press.
Kahraman, C., Ruan, D., & Doǧan, I. (2003). Fuzzy group decision-making for facility location selection. Information Sciences, 157, 135-153.
Kalayci, C. B., & Kaya, C. (2016). An ant colony system empowered variable neighborhood search algorithm for the vehicle routing problem with simultaneous pickup and delivery. Expert Systems with Applications, 66, 163-175.
Kalcsics, J., Nickel, S., Pozo, M. A., Puerto, J., & Rodríguez-Chía, A. M. (2014). The multicriteria p-facility median location problem on networks. European Journal of Operational Research, 235(3), 484-493.
Kannan, D., Khodaverdi, R., Olfat, L., Jafarian, A., & Diabat, A. (2013). Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain. Journal of Cleaner Production, 47, 355-367.
Karakatič, S., & Podgorelec, V. (2015). A survey of genetic algorithms for solving multi depot vehicle routing problem. Applied Soft Computing, 27, 519-532.
Lai, D. S., Demirag, O. C., & Leung, J. M. (2016). A tabu search heuristic for the heterogeneous vehicle routing problem on a multigraph. Transportation Research Part E: Logistics and Transportation Review, 86, 32-52.
Lenstra, J. K., & Kan, A. H. G. (1981). Complexity of vehicle routing and scheduling problems. Networks, 11(2), 221-227.
Miyazaki, M., & Une, H. (2005). Infectious waste management in Japan: A revised regulation and a management process in medical institutions. Waste management, 25(6), 616-621.
Nagy, G., & Salhi, S. (2007). Location-routing: Issues, models and methods. European Journal of Operational Research, 177(2), 649-672.
Nazari, A., Salarirad, M. M., & Bazzazi, A. A. (2012). Landfill site selection by decision-making tools based on fuzzy multi-attribute decision-making method. Environmental Earth Sciences, 65(6), 1631-1642.
Osman, I. H., & Christofides, N. (1994). Capacitated clustering problems by hybrid simulated annealing and tabu search. International Transactions in Operational Research, 1(3), 317-336.
Ozgen, D., & Gulsun, B. (2014). Combining possibilistic linear programming and fuzzy AHP for solving the multi-objective capacitated multi-facility location problem. Information Sciences, 268, 185-201.
Potvin, J. Y., & Rousseau, J. M. (1995). An exchange heuristic for routeing problems with time windows. Journal of the Operational Research Society, 46(12), 1433-1446.
Rahmani, A., & MirHassani, S. A. (2014). A hybrid firefly-genetic algorithm for the capacitated facility location problem. Information Sciences, 283, 70-78.
Razali, N. M. (2015). An efficient genetic algorithm for large scale vehicle routing problem subject to precedence constraints. Procedia - Social and Behavioral Sciences, 195, 1922-1931. doi: http://dx.doi.org/10.1016/j.sbspro.2015.06.203
de FSM Russo, R., & Camanho, R. (2015). Criteria in AHP: a systematic review of literature. Procedia Computer Science, 55, 1123-1132.
Singh, R. P., & Nachtnebel, H. P. (2016). Analytical hierarchy process (AHP) application for reinforcement of hydropower strategy in Nepal. Renewable and Sustainable Energy Reviews, 55, 43-58.
Solomon, M. M. (1987). Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations research, 35(2), 254-265.
Steiner, M. T. A., Datta, D., Neto, P. J. S., Scarpin, C. T., & Figueira, J. R. (2015). Multi-objective optimization in partitioning the healthcare system of Parana State in Brazil. Omega, 52, 53-64.
Tang, J., Ma, Y., Guan, J., & Yan, C. (2013). A max–min ant system for the split delivery weighted vehicle routing problem. Expert Systems with Applications, 40(18), 7468-7477.
Tavakkoli-Moghaddam, R., Safaei, N., Kah, M. M. O., & Rabbani, M. (2007). A new capacitated vehicle routing problem with split service for minimizing fleet cost by simulated annealing. Journal of the Franklin Institute, 344(5), 406-425.
Thangiah, S. R., Osman, I. H., & Sun, T. (1994). Hybrid genetic algorithm, simulated annealing and tabu search methods for vehicle routing problems with time windows. Computer Science Department, Slippery Rock University, Technical Report SRU CpSc-TR-94-27, 69.
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353.
Alumur, S., & Kara, B. Y. (2007). A new model for the hazardous waste location-routing problem. Computers & Operations Research, 34(5), 1406-1423.
Badri, M. A. (1999). Combining the analytic hierarchy process and goal programming for global facility location-allocation problem. International Journal of Production Economics, 62(3), 237-248.
Baker, B. M., & Ayechew, M. A. (2003). A genetic algorithm for the vehicle routing problem. Computers & Operations Research, 30(5), 787-800.
Birim, Ş. (2016). Vehicle Routing Problem with Cross Docking: A Simulated Annealing Approach. Procedia-Social and Behavioral Sciences, 235, 149-158.
Brandão, J. (2009). A deterministic tabu search algorithm for the fleet size and mix vehicle routing problem. European Journal of Operational Research, 195(3), 716-728.
Brandão, J. (2011). A tabu search algorithm for the heterogeneous fixed fleet vehicle routing problem. Computers & Operations Research, 38(1), 140-151.
Brandão de Oliveira, H. C., & Vasconcelos, G. C. (2010). A hybrid search method for the vehicle routing problem with time windows. Annals of Operations Research, 180(1), 125-144.
Choudhary, D., & Shankar, R. (2012). An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India. Energy, 42(1), 510-521.
Clarke, G., & Wright, J. W. (1964). Scheduling of vehicles from a central depot to a number of delivery points. Operations Research, 12(4), 568-581.
Correa, E. S., Steiner, M. T. A., Freitas, A. A., & Carnieri, C. (2001, July). A genetic algorithm for the p-median problem. In Proceedings of the 3rd Annual Conference on Genetic and Evolutionary Computation (pp. 1268-1275). Morgan Kaufmann Publishers Inc.
Dantrakul, S., Likasiri, C., & Pongvuthithum, R. (2014). Applied p-median and p-center algorithms for facility location problems. Expert Systems with Applications, 41(8), 3596-3604.
Dantzig, G. B., & Ramser, J. H. (1959). The truck dispatching problem. Management Science, 6(1), 80-91.
Dong, Q., & Cooper, O. (2016). A peer-to-peer dynamic adaptive consensus reaching model for the group AHP decision making. European Journal of Operational Research, 250(2), 521-530.
Etemadnia, H., Goetz, S. J., Canning, P., & Tavallali, M. S. (2015). Optimal wholesale facilities location within the fruit and vegetables supply chain with bimodal transportation options: An LP-MIP heuristic approach. European Journal of Operational Research, 244(2), 648-661.
Farahani, R. Z., SteadieSeifi, M., & Asgari, N. (2010). Multiple criteria facility location problems: A survey. Applied Mathematical Modelling, 34(7), 1689-1709.
Golmohammadi, A., Bani-Asadi, H., Zanjani, H., & Tikani, H. (2016). A genetic algorithm for preemptive scheduling of a single machine. International Journal of Industrial Engineering Computations, 7(4), 607-614.
Guastaroba, G., & Speranza, M. G. (2014). A heuristic for BILP problems: the single source capacitated facility location problem. European Journal of Operational Research, 238(2), 438-450.
Guo, P., Cheng, W., & Wang, Y. (2017). Hybrid evolutionary algorithm with extreme machine learning fitness function evaluation for two-stage capacitated facility location problems. Expert Systems with Applications, 71, 57-68.
Hanine, M., Boutkhoum, O., Tikniouine, A., & Agouti, T. (2016). Comparison of fuzzy AHP and fuzzy TODIM methods for landfill location selection. SpringerPlus, 5(1), 501.
Hansakul, A., Pitaksanurat, S., Srisatit, T., & Surit, P. (2010). Infectious waste management in the government hospitals by private transport sector: Case study of hospitals in the north east of Thailand. Journal of Environmental Research And Development, 4(4), 1070-1077.
Ho, W. (2007, October). Combining analytic hierarchy process and goal programming for logistics distribution network design. In Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on (pp. 714-719). IEEE.
He, T., Ho, W., Lee Ka Man, C., & Xu, X. (2012). A fuzzy AHP based integer linear programming model for the multi-criteria transshipment problem. The International Journal of Logistics Management, 23(1), 159-179.
Ho, W., Ho, G. T., Ji, P., & Lau, H. C. (2008). A hybrid genetic algorithm for the multi-depot vehicle routing problem. Engineering Applications of Artificial Intelligence, 21(4), 548-557.
Ho, W., Lee, C. K. M., & Ho, G. T. S. (2008). Optimization of the facility location-allocation problem in a customer-driven supply chain. Operations Management Research, 1(1), 69-79.
Holland, J. H. (1992). Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. MIT press.
Kahraman, C., Ruan, D., & Doǧan, I. (2003). Fuzzy group decision-making for facility location selection. Information Sciences, 157, 135-153.
Kalayci, C. B., & Kaya, C. (2016). An ant colony system empowered variable neighborhood search algorithm for the vehicle routing problem with simultaneous pickup and delivery. Expert Systems with Applications, 66, 163-175.
Kalcsics, J., Nickel, S., Pozo, M. A., Puerto, J., & Rodríguez-Chía, A. M. (2014). The multicriteria p-facility median location problem on networks. European Journal of Operational Research, 235(3), 484-493.
Kannan, D., Khodaverdi, R., Olfat, L., Jafarian, A., & Diabat, A. (2013). Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain. Journal of Cleaner Production, 47, 355-367.
Karakatič, S., & Podgorelec, V. (2015). A survey of genetic algorithms for solving multi depot vehicle routing problem. Applied Soft Computing, 27, 519-532.
Lai, D. S., Demirag, O. C., & Leung, J. M. (2016). A tabu search heuristic for the heterogeneous vehicle routing problem on a multigraph. Transportation Research Part E: Logistics and Transportation Review, 86, 32-52.
Lenstra, J. K., & Kan, A. H. G. (1981). Complexity of vehicle routing and scheduling problems. Networks, 11(2), 221-227.
Miyazaki, M., & Une, H. (2005). Infectious waste management in Japan: A revised regulation and a management process in medical institutions. Waste management, 25(6), 616-621.
Nagy, G., & Salhi, S. (2007). Location-routing: Issues, models and methods. European Journal of Operational Research, 177(2), 649-672.
Nazari, A., Salarirad, M. M., & Bazzazi, A. A. (2012). Landfill site selection by decision-making tools based on fuzzy multi-attribute decision-making method. Environmental Earth Sciences, 65(6), 1631-1642.
Osman, I. H., & Christofides, N. (1994). Capacitated clustering problems by hybrid simulated annealing and tabu search. International Transactions in Operational Research, 1(3), 317-336.
Ozgen, D., & Gulsun, B. (2014). Combining possibilistic linear programming and fuzzy AHP for solving the multi-objective capacitated multi-facility location problem. Information Sciences, 268, 185-201.
Potvin, J. Y., & Rousseau, J. M. (1995). An exchange heuristic for routeing problems with time windows. Journal of the Operational Research Society, 46(12), 1433-1446.
Rahmani, A., & MirHassani, S. A. (2014). A hybrid firefly-genetic algorithm for the capacitated facility location problem. Information Sciences, 283, 70-78.
Razali, N. M. (2015). An efficient genetic algorithm for large scale vehicle routing problem subject to precedence constraints. Procedia - Social and Behavioral Sciences, 195, 1922-1931. doi: http://dx.doi.org/10.1016/j.sbspro.2015.06.203
de FSM Russo, R., & Camanho, R. (2015). Criteria in AHP: a systematic review of literature. Procedia Computer Science, 55, 1123-1132.
Singh, R. P., & Nachtnebel, H. P. (2016). Analytical hierarchy process (AHP) application for reinforcement of hydropower strategy in Nepal. Renewable and Sustainable Energy Reviews, 55, 43-58.
Solomon, M. M. (1987). Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations research, 35(2), 254-265.
Steiner, M. T. A., Datta, D., Neto, P. J. S., Scarpin, C. T., & Figueira, J. R. (2015). Multi-objective optimization in partitioning the healthcare system of Parana State in Brazil. Omega, 52, 53-64.
Tang, J., Ma, Y., Guan, J., & Yan, C. (2013). A max–min ant system for the split delivery weighted vehicle routing problem. Expert Systems with Applications, 40(18), 7468-7477.
Tavakkoli-Moghaddam, R., Safaei, N., Kah, M. M. O., & Rabbani, M. (2007). A new capacitated vehicle routing problem with split service for minimizing fleet cost by simulated annealing. Journal of the Franklin Institute, 344(5), 406-425.
Thangiah, S. R., Osman, I. H., & Sun, T. (1994). Hybrid genetic algorithm, simulated annealing and tabu search methods for vehicle routing problems with time windows. Computer Science Department, Slippery Rock University, Technical Report SRU CpSc-TR-94-27, 69.
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353.