Achuthan, N. R., Caccetta, L., & Hill, S. P. (1996). A new subtour elimination constraint for the vehicle routing problem. European Journal of Operational Research, 91(3), 573-586.
Ball, M. O., Golden, B. L., Assad, A. A., & Bodin, L. D. (1983). Planning for truck fleet size in the presence of a common‐carrier option. Decision Sciences, 14(1), 103-120.
Barth, M., & Boriboonsomsin, K. (2007). Real-World CO2 Impacts of Traffic Congestion. In PREPARED FOR THE 87TH ANNUAL MEETING OF THE TRANSPORTATION RESEARCH BOARD.
Barth, M., Younglove, T., & Scora, G. (2005). Development of a heavy-duty diesel modal emissions and fuel consumption model.
Bektaş, T., & Laporte, G. (2011). The pollution-routing problem. Transportation Research Part B: Methodological, 45(8), 1232-1250.
Bolduc, M. C., Renaud, J., & Boctor, F. (2007). A heuristic for the routing and carrier selection problem. European Journal of Operational Research, 183(2), 926-932.
Bolduc, M. C., Renaud, J., Boctor, F., & Laporte, G. (2008). A perturbation metaheuristic for the vehicle routing problem with private fleet and common carriers. Journal of the Operational Research Society, 59(6), 776-787.
Borgulya, I. (2008). An algorithm for the capacitated vehicle routing problem with route balancing. Central European Journal of Operations Research, 16(4), 331-343.
Bosman, P. A., & Thierens, D. (2002). Multi-objective optimization with diversity preserving mixture-based iterated density estimation evolutionary algorithms. International Journal of Approximate Reasoning, 31(3), 259-289.
Bradstreet, L. (2011). The hypervolume indicator for multi-objective optimisation: calculation and use. Perth: University of Western Australia.
Castaneda L, J. F., Toro, E. M., & Gallego R, R. A. (2019). Iterated local search for the vehicle routing problem with a private fleet and a common carrier. Engineering Optimization, 1-18.
Chu, C. W. (2005). A heuristic algorithm for the truckload and less-than-truckload problem. European Journal of Operational Research, 165(3), 657-667.
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.
Dabia, S., Lai, D., & Vigo, D. (2019). An exact algorithm for a rich vehicle routing problem with private fleet and common carrier. Transportation Science, 53(4), 986-1000.
Dantzig, G. B., & Ramser, J. H. (1959). The truck dispatching problem. Management science, 6(1), 80-91.
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. A. M. T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE transactions on evolutionary computation, 6(2), 182-197.
Deb, K. (2014). Multi-objective optimization. In Search methodologies (pp. 403-449). Springer, Boston, MA.
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.
Euchi, J., Chabchoub, H., & Yassine, A. (2011). New evolutionary algorithm based on 2-opt local search to solve the vehicle routing problem with private fleet and common carrier. International Journal of Applied Metaheuristic Computing (IJAMC), 2(1), 58-82.
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.
Gass, S. I., & Assad, A. A. (2005). An annotated timeline of operations research: An informal history (Vol. 75). Springer Science & Business Media.
Galindres-Guancha, L., Toro-Ocampo, E., & Rendón, R. (2018). Multi-objective MDVRP solution considering route balance and cost using the ILS metaheuristic. International Journal of Industrial Engineering Computations, 9(1), 33-46.
Garetti, M., & Taisch, M. (2012). Sustainable manufacturing: trends and research challenges. Production planning & control, 23(2-3), 83-104.
Granada, M., Toro, E. M., & Gallego, R. (2019). An MIP formulation for the open location‐routing problem considering the topological characteristic of the solution‐paths. Networks, 74(4), 374-388.
Huang, K., & Hsu, C. P. (2011). A Lagrangian Heuristic for the Vehicle Routing Problems with the Private Fleet and the Common Carrier. Journal of the Eastern Asia Society for Transportation Studies, 9, 644-659.
Kant, G., Huijink, S., & Peeters, R. (2014). An Adaptable Variable Neighborhood Search for the Vehicle Routing Problem with Order Outsourcing.
Jozefowiez, N., Semet, F., & Talbi, E. G. (2009). An evolutionary algorithm for the vehicle routing problem with route balancing. European Journal of Operational Research, 195(3), 761-769.
Jozefowiez, N., Semet, F., & Talbi, E. G. (2005, October). Enhancements of NSGA II and its application to the vehicle routing problem with route balancing. In International Conference on Artificial Evolution (Evolution Artificielle) (pp. 131-142). Springer, Berlin, Heidelberg.
Jozefowiez, N., Semet, F., & Talbi, E. G. (2002, September). Parallel and hybrid models for multi-objective optimization: Application to the vehicle routing problem. In International Conference on Parallel Problem Solving from Nature (pp. 271-280). Springer, Berlin, Heidelberg.
Jozefowiez, N., Semet, F., & Talbi, E. G. (2007). Target aiming Pareto search and its application to the vehicle routing problem with route balancing. Journal of Heuristics, 13(5), 455-469.
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.
Klincewicz, J. G., Luss, H., & Pilcher, M. G. (1990). Fleet size planning when outside carrier services are available. Transportation Science, 24(3), 169-182.
Kucukoglu, I., Ene, S., Aksoy, A., & Ozturk, N. (2013). Green capacitated vehicle routing problem fuel consumption optimization model. Computational Engineering Research, 3, 16-23.
Kuo, Y. (2010). Using simulated annealing to minimize fuel consumption for the time-dependent vehicle routing problem. Computers & Industrial Engineering, 59(1), 157-165.
Lacomme, P., Prins, C., Prodhon, C., & Ren, L. (2015). A multi-start split based path relinking (MSSPR) approach for the vehicle routing problem with route balancing. Engineering Applications of Artificial Intelligence, 38, 237-251.
Laporte, G., Desrochers, M., & Nobert, Y. (1984). Two exact algorithms for the distance‐constrained vehicle routing problem. Networks, 14(1), 161-172.
Maden, W., Eglese, R., & Black, D. (2010). Vehicle routing and scheduling with time-varying data: A case study. Journal of the Operational Research Society, 61(3), 515-522.
Matl, P., Hartl, R. F., & Vidal, T. (2018). Workload equity in vehicle routing problems: A survey and analysis. Transportation Science, 52(2), 239-260.
Moon, I., Lee, J. H., & Seong, J. (2012). Vehicle routing problem with time windows considering overtime and outsourcing vehicles. Expert Systems with Applications, 39(18), 13202-13213.
Osman, I. H. (1993). Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem. Annals of operations research, 41(4), 421-451.
Oyola, J., & Løkketangen, A. (2014). GRASP-ASP: An algorithm for the CVRP with route balancing. Journal of Heuristics, 20(4), 361-382.
Palmer, A. (2007). The development of an integrated routing and carbon dioxide emissions model for goods vehicles.
Pasia, J. M., Doerner, K. F., Hartl, R. F., & Reimann, M. (2007, April). A population-based local search for solving a bi-objective vehicle routing problem. In European conference on Evolutionary computation in combinatorial optimization (pp. 166-175). Springer, Berlin, Heidelberg.
Pasia, J. M., Doerner, K. F., Hartl, R. F., & Reimann, M. (2007, September). Solving a bi-objective vehicle routing problem by pareto-ant colony optimization. In International Workshop on Engineering Stochastic Local Search Algorithms (pp. 187-191). Springer, Berlin, Heidelberg.
Penna, P. H. V., Subramanian, A., & Ochi, L. S. (2013). An iterated local search heuristic for the heterogeneous fleet vehicle routing problem. Journal of Heuristics, 19(2), 201-232.
Potvin, J. Y., & Naud, M. A. (2011). Tabu search with ejection chains for the vehicle routing problem with private fleet and common carrier. Journal of the operational research society, 62(2), 326-336.
Reiter, P., & Gutjahr, W. J. (2012). Exact hybrid algorithms for solving a bi-objective vehicle routing problem. Central European Journal of Operations Research, 20(1), 19-43.
Rendón, R. A. G., Ocampo, E. M. T., & Zuluaga, A. H. E. (2015). Técnicas heurísticas y metaheurísticas. Universidad Tecnológica de Pereira. Vicerrectoría de Investigaciones, Innovación y Extensión. Ingenierías Eléctrica, Electrónica, Física y Ciencias de la Computación.
Sarpong, B. M., Artigues, C., & Jozefowiez, N. (2013, September). Column generation for bi-objective vehicle routing problems with a min-max objective.
Schott, J. R. (1995). Fault tolerant design using single and multicriteria genetic algorithm optimization (No. AFIT/CI/CIA-95-039). Air Force Inst of Tech Wright-Patterson AFB OH.
Scora, G., & Barth, M. (2006). Comprehensive modal emissions model (cmem), version 3.01. User guide. Centre for environmental research and technology. University of California, Riverside, 1070.
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.
Tian, Y., Cheng, R., Zhang, X., & Jin, Y. (2017). PlatEMO: A MATLAB platform for evolutionary multi-objective optimization [educational forum]. IEEE Computational Intelligence Magazine, 12(4), 73-87.
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.
Toro-Ocampo, E. M., Franco-Baquero, J. F., & Gallego-Rendón, R. A. (2016). Modelo matemático para resolver el problema de localización y ruteo con restricciones de capacidad considerando flota propia y subcontratada. Ingeniería, investigación y tecnología, 17(3), 357-369.
Ubeda, S., Arcelus, F. J., & Faulin, J. (2011). Green logistics at Eroski: A case study. International Journal of Production Economics, 131(1), 44-51.
Uchoa, E., Pecin, D., Pessoa, A., Poggi, M., Vidal, T., & Subramanian, A. (2017). New benchmark instances for the capacitated vehicle routing problem. European Journal of Operational Research, 257(3), 845-858.
Wang, X., & Regan, A. C. (2009). On the convergence of a new time window discretization method for the traveling salesman problem with time window constraints. Computers & Industrial Engineering, 56(1), 161-164.
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.