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How to cite this paper
APA: Toro, E., Franco, J., Echeverri, M., Guimarães, F & Rendón, R. (2017). Green open location-routing problem considering economic and environmental costs. International Journal of Industrial Engineering Computations, 8(2), 203-216.
Chicago/Turabian: Toro, E., Franco, J., Echeverri, M., Guimarães, F & Rendón, R. 2017. "Green open location-routing problem considering economic and environmental costs." International Journal of Industrial Engineering Computations 8, no. 2 (2017): 203-216.
AMA: Toro, E., Franco, J., Echeverri, M., Guimarães, F & Rendón, R. Green open location-routing problem considering economic and environmental costs. International Journal of Industrial Engineering Computations. 2017;8(2):203-216.
References
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Bazaraa, M. S., Jarvis, J. J., & Sherali, H. D. (2011). Linear programming and network flows. John Wiley & Sons.
Bektaş, T., & Laporte, G. (2011). The pollution-routing problem. Transportation Research Part B: Methodological, 45(8), 1232-1250.
Bodin, L., Golden, B., and Assad, A. (1983). Routing and scheduling of vehicles and crews: the state of the art. Computers and Operations Research, 10(2), 63 – 211.
Boriboonsomsin, K., Vu, A., & Barth, M. (2010). Eco-driving: pilot evaluation of driving behavior changes among us drivers. University of California Transportation Center.
Braekers, K., Ramaekers, K., & Van Nieuwenhuyse, I. (2015). The vehicle routing problem: State of the art classification and review. Computers & Industrial Engineering, 99, 300-313.
Cohon, J. L., & Marks, D. H. (1975). A review and evaluation of multiobjective programing techniques. Water Resources Research, 11(2), 208-220.
Daniel, S. E., Diakoulaki, D. C., & Pappis, C. P. (1997). Operations research and environmental planning. European Journal of Operational Research, 102(2), 248-263.
Demir, E., Bektaş, T., & Laporte, G. (2012). An adaptive large neighborhood search heuristic for the pollution-routing problem. European Journal of Operational Research, 223(2), 346-359.
Demir, E., Bektaş, T., & Laporte, G. (2014). The bi-objective pollution-routing problem. European Journal of Operational Research, 232(3), 464-478.
Dueck, G., & Scheuer, T. (1990). Threshold accepting: a general purpose optimization algorithm appearing superior to simulated annealing. Journal of Computational Physics, 90(1), 161-175.
Ehrgott, M., & Gandibleux, X. (2003). Multiobjective combinatorial optimization—theory, methodology, and applications. In Multiple criteria optimization: State of the art annotated bibliographic surveys (pp. 369-444). Springer US.
Erdogan, S. and Miller-Hooks, E. (2012). A green vehicle routing problem. Transportation Research Part E: Logistics and Transportation Review, 48(1), 100–114.
Figliozzi, M. A. (2010). An iterative route construction and improvement algorithm for the vehicle routing problem with soft time windows. Transportation Research Part C: Emerging Technologies, 18(5), 668-679.
Fourer, R., Gay, D. M., & Kernighan, B. W. (2002). AMPL: A Modeling Language for Mathematical Programming. Brooks/Cole-Thomson, 2nd edition.
Neto, J. Q. F., Walther, G., Bloemhof, J., Van Nunen, J. A. E. E., & Spengler, T. (2009). A methodology for assessing eco-efficiency in logistics networks.European Journal of Operational Research, 193(3), 670-682.
Golden, B. L., Raghavan, S., & Wasil, E. A. (Eds.). (2008). The vehicle routing problem: latest advances and new challenges (Vol. 43). Springer Science & Business Media.
Gouvermment of Canada (2015). Fuel consumption guide.
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.
ILOG, S. (2008). CPLEX optimization subroutine library guide and reference.System v11. 0 User’s Guide.
Jemai, J., Zekri, M., & Mellouli, K. (2012, April). An NSGA-II algorithm for the green vehicle routing problem. In European Conference on Evolutionary Computation in Combinatorial Optimization (pp. 37-48). Springer Berlin Heidelberg.
Kara, I., Kara, B. Y., & Yetis, M. K. (2007, August). Energy minimizing vehicle routing problem. In International Conference on Combinatorial Optimization and Applications (pp. 62-71). Springer Berlin Heidelberg.
Kucukoglu, I., Ene, S., Aksoy, A., & Ozturk, N. (2013). Green capacitated vehicle routing problem fuel consumption optimization model. Computational Engineering Research, 3, 16-23.
Lalla-Ruiz, E., Expósito-Izquierdo, C., Taheripour, S., & Voß, S. (2016). An improved formulation for the multi-depot open vehicle routing problem. OR Spectrum, 38(1), 175-187.
Lavorato, M., Franco, J. F., Rider, M. J., & Romero, R. (2012). Imposing radiality constraints in distribution system optimization problems. IEEE Transactions on Power Systems, 27(1), 172-180.
Lin, C., Choy, K. L., Ho, G. T., Chung, S. H., & Lam, H. Y. (2014). Survey of green vehicle routing problem: past and future trends. Expert Systems with Applications, 41(4), 1118-1138.
Liu, R., & Jiang, Z. (2012). The close–open mixed vehicle routing problem.European Journal of Operational Research, 220(2), 349-360.
Marler, R. T., & Arora, J. S. (2009). Multi-objective optimization: concepts and methods for engineering. VDM Publishing.
Miettinen, K. (1999). Nonlinear Multiobjective Optimization, volume 12 of International Series in Operations Research and Management Science.
Mirabi, M., Ghomi, S. F., & Jolai, F. (2010). Efficient stochastic hybrid heuristics for the multi-depot vehicle routing problem. Robotics and Computer-Integrated Manufacturing, 26(6), 564-569.
Palmer, A. (2007). The Development of an Integrated Routing and Carbon Dioxide Emissions Model for Goods Vehicles. PhD thesis, School of Management, Cranfield University.
Pradenas, L., Oportus, B., & Parada, V. (2013). Mitigation of greenhouse gas emissions in vehicle routing problems with backhauling. Expert Systems with Applications, 40(8), 2985-2991.
Prins, C., Prodhon, C., & Calvo, R. W. (2006). Solving the capacitated location-routing problem by a GRASP complemented by a learning process and a path relinking. 4OR, 4(3), 221-238.
Prins, C., Prodhon, C., Ruiz, A., Soriano, P., & Wolfler Calvo, R. (2007). Solving the capacitated location-routing problem by a cooperative Lagrangean relaxation-granular tabu search heuristic. Transportation Science, 41(4), 470-483.
Schrage, L. (1981). Formulation and structure of more complex/realistic routing and scheduling problems. Networks, 11(2), 229-232.
SENDECO2 (2014). The European bourse for European Unit Allowances ( EUA ) and Carbon Credits ( CER’s ).
Suzuki, Y. (2011). A new truck-routing approach for reducing fuel consumption and pollutants emission. Transportation Research Part D: Transport and Environment, 16(1), 73-77.
Tarantilis, C. D., & Kiranoudis, C. T. (2002). Distribution of fresh meat. Journal of Food Engineering, 51(1), 85-91.
Toro, E., Escobar, A., & Granada, M. (2016). Literature Review on the Vehicle Routing Problem in the Green Transportation Context. Luna Azul, 42(1), 362 – 387.
Toth, P., & Vigo, D. (Eds.). (2014). Vehicle routing: problems, methods, and applications (Vol. 18). Siam.
Transportation Research Institute (2014). Large drop in fuel economy in september.
Trigeorgis, L. (1996). Real options: Managerial flexibility and strategy in resource allocation. MIT press.
Tuzun, D., & Burke, L. I. (1999). A two-phase tabu search approach to the location routing problem. European journal of operational research, 116(1), 87-99.
Ubeda, S., Arcelus, F. J., & Faulin, J. (2011). Green logistics at Eroski: A case study. International Journal of Production Economics, 131(1), 44-51.
Xiao, Y., Zhao, Q., Kaku, I., & Xu, Y. (2012). Development of a fuel consumption optimization model for the capacitated vehicle routing problem.Computers & Operations Research, 39(7), 1419-1431.
Yao, B., Hu, P., Zhang, M., & Tian, X. (2014). Improved ant colony optimization for seafood product delivery routing problem. PROMET-Traffic&Transportation,26(1), 1-10.
Vincent, F. Y., & Lin, S. Y. (2015). A simulated annealing heuristic for the open location-routing problem. Computers & Operations Research, 62, 184-196.
Bazaraa, M. S., Jarvis, J. J., & Sherali, H. D. (2011). Linear programming and network flows. John Wiley & Sons.
Bektaş, T., & Laporte, G. (2011). The pollution-routing problem. Transportation Research Part B: Methodological, 45(8), 1232-1250.
Bodin, L., Golden, B., and Assad, A. (1983). Routing and scheduling of vehicles and crews: the state of the art. Computers and Operations Research, 10(2), 63 – 211.
Boriboonsomsin, K., Vu, A., & Barth, M. (2010). Eco-driving: pilot evaluation of driving behavior changes among us drivers. University of California Transportation Center.
Braekers, K., Ramaekers, K., & Van Nieuwenhuyse, I. (2015). The vehicle routing problem: State of the art classification and review. Computers & Industrial Engineering, 99, 300-313.
Cohon, J. L., & Marks, D. H. (1975). A review and evaluation of multiobjective programing techniques. Water Resources Research, 11(2), 208-220.
Daniel, S. E., Diakoulaki, D. C., & Pappis, C. P. (1997). Operations research and environmental planning. European Journal of Operational Research, 102(2), 248-263.
Demir, E., Bektaş, T., & Laporte, G. (2012). An adaptive large neighborhood search heuristic for the pollution-routing problem. European Journal of Operational Research, 223(2), 346-359.
Demir, E., Bektaş, T., & Laporte, G. (2014). The bi-objective pollution-routing problem. European Journal of Operational Research, 232(3), 464-478.
Dueck, G., & Scheuer, T. (1990). Threshold accepting: a general purpose optimization algorithm appearing superior to simulated annealing. Journal of Computational Physics, 90(1), 161-175.
Ehrgott, M., & Gandibleux, X. (2003). Multiobjective combinatorial optimization—theory, methodology, and applications. In Multiple criteria optimization: State of the art annotated bibliographic surveys (pp. 369-444). Springer US.
Erdogan, S. and Miller-Hooks, E. (2012). A green vehicle routing problem. Transportation Research Part E: Logistics and Transportation Review, 48(1), 100–114.
Figliozzi, M. A. (2010). An iterative route construction and improvement algorithm for the vehicle routing problem with soft time windows. Transportation Research Part C: Emerging Technologies, 18(5), 668-679.
Fourer, R., Gay, D. M., & Kernighan, B. W. (2002). AMPL: A Modeling Language for Mathematical Programming. Brooks/Cole-Thomson, 2nd edition.
Neto, J. Q. F., Walther, G., Bloemhof, J., Van Nunen, J. A. E. E., & Spengler, T. (2009). A methodology for assessing eco-efficiency in logistics networks.European Journal of Operational Research, 193(3), 670-682.
Golden, B. L., Raghavan, S., & Wasil, E. A. (Eds.). (2008). The vehicle routing problem: latest advances and new challenges (Vol. 43). Springer Science & Business Media.
Gouvermment of Canada (2015). Fuel consumption guide.
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.
ILOG, S. (2008). CPLEX optimization subroutine library guide and reference.System v11. 0 User’s Guide.
Jemai, J., Zekri, M., & Mellouli, K. (2012, April). An NSGA-II algorithm for the green vehicle routing problem. In European Conference on Evolutionary Computation in Combinatorial Optimization (pp. 37-48). Springer Berlin Heidelberg.
Kara, I., Kara, B. Y., & Yetis, M. K. (2007, August). Energy minimizing vehicle routing problem. In International Conference on Combinatorial Optimization and Applications (pp. 62-71). Springer Berlin Heidelberg.
Kucukoglu, I., Ene, S., Aksoy, A., & Ozturk, N. (2013). Green capacitated vehicle routing problem fuel consumption optimization model. Computational Engineering Research, 3, 16-23.
Lalla-Ruiz, E., Expósito-Izquierdo, C., Taheripour, S., & Voß, S. (2016). An improved formulation for the multi-depot open vehicle routing problem. OR Spectrum, 38(1), 175-187.
Lavorato, M., Franco, J. F., Rider, M. J., & Romero, R. (2012). Imposing radiality constraints in distribution system optimization problems. IEEE Transactions on Power Systems, 27(1), 172-180.
Lin, C., Choy, K. L., Ho, G. T., Chung, S. H., & Lam, H. Y. (2014). Survey of green vehicle routing problem: past and future trends. Expert Systems with Applications, 41(4), 1118-1138.
Liu, R., & Jiang, Z. (2012). The close–open mixed vehicle routing problem.European Journal of Operational Research, 220(2), 349-360.
Marler, R. T., & Arora, J. S. (2009). Multi-objective optimization: concepts and methods for engineering. VDM Publishing.
Miettinen, K. (1999). Nonlinear Multiobjective Optimization, volume 12 of International Series in Operations Research and Management Science.
Mirabi, M., Ghomi, S. F., & Jolai, F. (2010). Efficient stochastic hybrid heuristics for the multi-depot vehicle routing problem. Robotics and Computer-Integrated Manufacturing, 26(6), 564-569.
Palmer, A. (2007). The Development of an Integrated Routing and Carbon Dioxide Emissions Model for Goods Vehicles. PhD thesis, School of Management, Cranfield University.
Pradenas, L., Oportus, B., & Parada, V. (2013). Mitigation of greenhouse gas emissions in vehicle routing problems with backhauling. Expert Systems with Applications, 40(8), 2985-2991.
Prins, C., Prodhon, C., & Calvo, R. W. (2006). Solving the capacitated location-routing problem by a GRASP complemented by a learning process and a path relinking. 4OR, 4(3), 221-238.
Prins, C., Prodhon, C., Ruiz, A., Soriano, P., & Wolfler Calvo, R. (2007). Solving the capacitated location-routing problem by a cooperative Lagrangean relaxation-granular tabu search heuristic. Transportation Science, 41(4), 470-483.
Schrage, L. (1981). Formulation and structure of more complex/realistic routing and scheduling problems. Networks, 11(2), 229-232.
SENDECO2 (2014). The European bourse for European Unit Allowances ( EUA ) and Carbon Credits ( CER’s ).
Suzuki, Y. (2011). A new truck-routing approach for reducing fuel consumption and pollutants emission. Transportation Research Part D: Transport and Environment, 16(1), 73-77.
Tarantilis, C. D., & Kiranoudis, C. T. (2002). Distribution of fresh meat. Journal of Food Engineering, 51(1), 85-91.
Toro, E., Escobar, A., & Granada, M. (2016). Literature Review on the Vehicle Routing Problem in the Green Transportation Context. Luna Azul, 42(1), 362 – 387.
Toth, P., & Vigo, D. (Eds.). (2014). Vehicle routing: problems, methods, and applications (Vol. 18). Siam.
Transportation Research Institute (2014). Large drop in fuel economy in september.
Trigeorgis, L. (1996). Real options: Managerial flexibility and strategy in resource allocation. MIT press.
Tuzun, D., & Burke, L. I. (1999). A two-phase tabu search approach to the location routing problem. European journal of operational research, 116(1), 87-99.
Ubeda, S., Arcelus, F. J., & Faulin, J. (2011). Green logistics at Eroski: A case study. International Journal of Production Economics, 131(1), 44-51.
Xiao, Y., Zhao, Q., Kaku, I., & Xu, Y. (2012). Development of a fuel consumption optimization model for the capacitated vehicle routing problem.Computers & Operations Research, 39(7), 1419-1431.
Yao, B., Hu, P., Zhang, M., & Tian, X. (2014). Improved ant colony optimization for seafood product delivery routing problem. PROMET-Traffic&Transportation,26(1), 1-10.
Vincent, F. Y., & Lin, S. Y. (2015). A simulated annealing heuristic for the open location-routing problem. Computers & Operations Research, 62, 184-196.