How to cite this paper
Riaño, H., Escobar, J & Clavijo-Buritica, N. (2022). A new metaheuristic approach for the meat routing problem by considering heterogeneous fleet with time windows.International Journal of Industrial Engineering Computations , 13(4), 661-676.
Refrences
Aguiar, L. K. (2020). The livestock sector 2020: consumer perspectives I. Universidade Federal do Rio Grande do Sul (UFRGS), 91, 222.
Amorim, P., & Almada-Lobo, B. (2014). The impact of food perishability issues in the vehicle routing problem. Computers & Industrial Engineering, 67, 223-233.
Amorim, P., Parragh, S. N., Sperandio, F., & Almada-Lobo, B. (2014). A rich vehicle routing problem dealing with perishable food: a case study. Top, 22(2), 489-508.
Barros, L., Linfati, R., & Escobar, J. W. (2020). An exact approach for the consistent vehicle routing problem (ConVRP). Advances in Production Engineering & Management, 15(3), 255-266.
Belo-Filho, M. A. F., Amorim, P., & Almada-Lobo, B. (2015). An adaptive large neighbourhood search for the operational integrated production and distribution problem of perishable products. International Journal of Production Research, 53(20), 6040-6058.
Bernal, J., Escobar, J. W., & Linfati, R. (2017). A granular tabu search algorithm for a real case study of a vehicle routing problem with a heterogeneous fleet and time windows. Journal of Industrial Engineering and Management, 10(4), 646-662.
Bernal-Moyano, J. A., Escobar, J. W., Marín-Moreno, C., Linfati, R., & Gatica, G. (2017). A comparison of trajectory granular based algorithms for the location-routing problem with heterogeneous fleet (LRPH). Dyna, 84(200), 193-201.
Bernal, J., Escobar, J. W., Paz, J. C., Linfati, R., & Gatica, G. (2018). A probabilistic granular tabu search for the distance constrained capacitated vehicle routing problem. International Journal of Industrial and Systems Engineering, 29(4), 453-477.
Bocarejo, J. P. (2020). Congestion in Latin American Cities: Innovative Approaches for a Critical Issue.
Bolanos, R., Escobar, J., & Echeverri, M. (2018). A metaheuristic algorithm for the multi-depot vehicle routing problem with heterogeneous fleet. International Journal of Industrial Engineering Computations, 9(4), 461-478.
Chávez, J., Escobar, J., Echeverri, M., & Meneses, C. (2018). A heuristic algorithm based on tabu search for vehicle routing problems with backhauls. Decision Science Letters, 7(2), 171-180.
Chen, H. K., Hsueh, C. F., & Chang, M. S. (2009). Production scheduling and vehicle routing with time windows for perishable food products. Computers & operations research, 36(7), 2311-2319.
Chowmali, W., & Sukto, S. (2020). A novel two-phase approach for solving the multi-compartment vehicle routing problem with a heterogeneous fleet of vehicles: a case study on fuel delivery. Decision Science Letters, 9(1), 77-90.
Cordeau, J. F., Gendreau, M., & Laporte, G. (1997). A tabu search heuristic for periodic and multi‐depot vehicle routing problems. Networks: An International Journal, 30(2), 105-119.
Escobar, J. W., Bravo, J. J., & Vidal, C. J. (2012). Optimización de redes de distribución de productos de consumo masivo en condiciones de riesgo. In Proceedings of XXXIII Congreso Nacional de Estadística e Investigación Operativa (SEIO), Madrid, Spain.
Escobar, J.W., & Linfati, R. (2012). Un algoritmo metaheurístico basado en recocido simulado con espacio de búsqueda granular para el problema de localización y ruteo con restricciones de capacidad. Revista Ingenierías Universidad de Medellín, 11(21), 139-150.
Escobar, J.W., Linfati, R., & Toth, P. (2013). A two-phase hybrid heuristic algorithm for the capacitated location-routing problem. Computers & Operations Research, 40(1), 70–79.
Escobar, J.W., Linfati, R., Toth, P., & Baldoquin, M. G. (2014a). A hybrid granular tabu search algorithm for the multi-depot vehicle routing problem. Journal of heuristics, 20(5), 483–509.
Escobar, J. W., Linfati, R., Baldoquin, M. G., & Toth, P. (2014b). A Granular Variable Tabu Neighborhood Search for the capacitated location-routing problem. Transportation Research Part B: Methodological, 67, 344–356.
Escobar, J.W., Linfati, R., & Adarme-Jaimes, W. (2015a). A hybrid metaheuristic algorithm for the capacitated location routing problem. Dyna, 82(189), 243–251.
Escobar, J. W., Linfati, R., & Adarme Jaimes, W. (2015b). Problema de localización y ruteo con restricciones de capacidad: Revisión de la Literatura. Revista Facultad de Ingeniería, 24(39), 85-98
Escobar, J.W., Adarme-Jaimes, W., & Clavijo-Buriticá, N. (2017). Comparative analysis of granular neighborhoods in a Tabu Search for the vehicle routing problem with heterogeneous fleet and variable costs (HFVRP). Revista Facultad de Ingeniería, 26(46), 93-104.
Escobar-Falcón, L., Alvarez-Martinez, D., Wilmer-Escobar, J., & Granada-Echeverri, M. (2021). A specialized genetic algorithm for the fuel consumption heterogeneous fleet vehicle routing problem with bidimensional packing constraints. International Journal of Industrial Engineering Computations, 12(2), 191-204.
Esmaili, M., & Sahraeian, R. (2017). A new bi-objective model for a two-echelon capacitated vehicle routing problem for perishable products with the environmental factor. International Journal of Engineering, 30(4), 523-531.
Flamini, M., Nigro, M., & Pacciarelli, D. (2011). Assessing the value of information for retail distribution of perishable goods. European Transport Research Review, 3(2), 103-112.
Ganji, M., Kazemipoor, H., Molana, S. M. H., & Sajadi, S. M. (2020). A green multi-objective integrated scheduling of production and distribution with heterogeneous fleet vehicle routing and time windows. Journal of Cleaner Production, 259, 120824.
Ghannadpour, S. F., & Zarrabi, A. (2019). Multi-objective heterogeneous vehicle routing and scheduling problem with energy minimizing. Swarm and evolutionary computation, 44, 728-747.
Hanum, F., Hadi, M., Aman, A., & Bakhtiar, T. (2019). Vehicle routing problems in rice-for-the-poor distribution. Decision Science Letters, 8(3), 323-338.
Hashimoto, H., Ibaraki, T., Imahori, S., & Yagiura, M. (2006). The vehicle routing problem with flexible time windows and traveling times. Discrete Applied Mathematics, 154(16), 2271-2290.
Helsgaun, K. (2000). An effective implementation of the Lin–Kernighan traveling salesman heuristic. European Journal of Operational Research, 126(1), 106–130.
Hsu, C. I., Hung, S. F., & Li, H. C. (2007). Vehicle routing problem with time-windows for perishable food delivery. Journal of food engineering, 80(2), 465-475.
Jafari Nozar, F., & Behnamian, J. (2020). Hyper-heuristic for integrated due-window scheduling and vehicle routing problem for perishable products considering production quality. Engineering Optimization, 1-20.
Kang, H. Y., & Lee, A. H. (2018). An Enhanced Approach for the Multiple Vehicle Routing Problem with Heterogeneous Vehicles and a Soft Time Window. Symmetry, 10(11), 650.
Linfati, R., Escobar, J. W., & Gatica, G. (2014a). Un algoritmo metaheurístico para el problema de localización y ruteo con flota heterogénea. Ingeniería y Ciencia, 10(19), 55-76.
Linfati, R., Escobar, J. W., & Cuevas, B. (2014b). An algorithm based on granular tabu search for the problem of balancing public bikes by using multiple vehicles. Dyna, 81(186), 284-294.
Liu, G., Hu, J., Yang, Y., Xia, S., & Lim, M. K. (2020). Vehicle routing problem in cold Chain logistics: A joint distribution model with carbon trading mechanisms. Resources, Conservation and Recycling, 156, 104715.
Ma, Z. J., Wu, Y., & Dai, Y. (2017). A combined order selection and time-dependent vehicle routing problem with time widows for perishable product delivery. Computers & Industrial Engineering, 114, 101-113.
Molina, J. C., Salmeron, J. L., & Eguia, I. (2020a). An ACS-based memetic algorithm for the heterogeneous vehicle routing problem with time windows. Expert Systems with Applications, 157, 113379.
Molina, J. C., Salmeron, J. L., Eguia, I., & Racero, J. (2020b). The heterogeneous vehicle routing problem with time windows and a limited number of resources. Engineering Applications of Artificial Intelligence, 94, 103745.
Nagle, S. K., & Panneerselvam, R. (2018). Study of Crossover operators of Genetic Algorithm& Development of New Crossover Operator to Solve Heterogeneous Vehicle Routing Problem with Time Windows. International Journal of Production Technology and Management (IJPTM), 9(2).
Nosrati, M., & Khamseh, A. (2020). Bi objective hybrid vehicle routing problem with alternative paths and reliability. Decision Science Letters, 9(2), 145-162.
Osvald, A., & Stirn, L. Z. (2008). A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food. Journal of food engineering, 85(2), 285-295.
Paz, J., Orozco, J., Salinas, J., Buriticá, N., & Escobar, J. (2015). Redesign of a supply network by considering stochastic demand. International Journal of Industrial Engineering Computations, 6(4), 521-528.
Puenayán, D. E., Londoño, J. C., Escobar, J. W., & Linfati, R. (2014). Un algoritmo basado en búsqueda tabú granular para la solución de un problema de ruteo de vehículos considerando flota heterogénea. Revista Ingenierías Universidad de Medellín, 13(25), 81-98.
Qin, G., Tao, F., & Li, L. (2019). A vehicle routing optimization problem for cold chain logistics considering customer satisfaction and carbon emissions. International journal of environmental research and public health, 16(4), 576.
Rahbari, A., Nasiri, M. M., Werner, F., Musavi, M., & Jolai, F. (2019). The vehicle routing and scheduling problem with cross-docking for perishable products under uncertainty: Two robust bi-objective models. Applied Mathematical Modelling, 70, 605-625.
Rezaei, N., Ebrahimnejad, S., Moosavi, A., & Nikfarjam, A. (2019). A green vehicle routing problem with time windows considering the heterogeneous fleet of vehicles: two metaheuristic algorithms. European Journal of Industrial Engineering, 13(4), 507-535.
Ritchie, H., & Roser, M. (2020). Environmental impacts of food production. Our world in data.
Rodado, D., Escobar, J., García-Cáceres, R., & Atencio, F. (2017). A mathematical model for the product mixing and lot-sizing problem by considering stochastic demand. International Journal of Industrial Engineering Computations, 8(2), 237-250.
Sahraeian, R., & Esmaeili, M. (2018). A multi-objective two-echelon capacitated vehicle routing problem for perishable products. Journal of Industrial and Systems Engineering, 11(2), 62-84.
Schroeder, H., Boykoff, M. T., & Spiers, L. (2012). Equity and state representations in climate negotiations. Nature Climate Change, 2(12), 834-836.
Sepúlveda, J., Escobar, J. W., & Adarme-Jaimes, W. (2014). An algorithm for the routing problem with split deliveries and time windows (SDVRPTW) applied on retail SME distribution activities. Dyna, 81(187), 223-231.
Song, B. D., & Ko, Y. D. (2016). A vehicle routing problem of both refrigerated-and general-type vehicles for perishable food products delivery. Journal of food engineering, 169, 61-71.
Song, M. X., Li, J. Q., Han, Y. Q., Han, Y. Y., Liu, L. L., & Sun, Q. (2020). Metaheuristics for solving the vehicle routing problem with the time windows and energy consumption in cold chain logistics. Applied Soft Computing, 95, 106561.
Susilawati, E., Mawengkang, H., & Efendi, S. (2018). An integer programming model for solving heterogeneous vehicle routing problem with hard time window considering service choice. In IOP Conference Series: Materials Science and Engineering (Vol. 300, No. 1, p. 012023). IOP Publishing.
Taillard, É. D., Laporte, G., & Gendreau, M. (1996). Vehicle routing with multiple use of vehicles. Journal of the Operational research society, 47(8), 1065-1070.
Taniguchi, E., Thompson, E., Yamada, T., van Duin, J., & Logistics, C. (2001). Network Modelling and Intelligent Transport Systems, Pergamon, Oxford.
Tirkolaee, E. B., Hadian, S., Weber, G. W., & Mahdavi, I. (2020). A robust green traffic‐based routing problem for perishable products distribution. Computational Intelligence, 36(1), 80-101.
Toth, P., & Vigo, D. (2003). The granular tabu search and its application to the vehicle-routing problem. Informs Journal on computing, 15(4), 333–346.
Utama, D. M., Dewi, S. K., Wahid, A., & Santoso, I. (2020). The vehicle routing problem for perishable goods: A systematic review. Cogent Engineering, 7(1), 1816148.
Vélez, Y. S., Varela, H. P., Londoño, J. C., & Escobar, J. W. (2021). Redesign of supply chains for agricultural companies considering multiple scenarios by the methodology of sample average approximation. International Journal of Business Performance and Supply Chain Modelling, 12(1), 44-68.
Wang, Z., & Wen, P. (2020). Optimization of a low-carbon two-echelon heterogeneous-fleet vehicle routing for cold chain logistics under mixed time window. Sustainability, 12(5), 1967.
Wu, Y., Zheng, B., & Zhou, X. (2020). A Disruption Recovery Model for Time-Dependent Vehicle Routing Problem With Time Windows in Delivering Perishable Goods. IEEE Access, 8, 189614-189631.
Yu, Y., Wang, S., Wang, J., & Huang, M. (2019). A branch-and-price algorithm for the heterogeneous fleet green vehicle routing problem with time windows. Transportation Research Part B: Methodological, 122, 511-527.
Zulvia, F. E., Kuo, R. J., & Nugroho, D. Y. (2020). A many-objective gradient evolution algorithm for solving a green vehicle routing problem with time windows and time dependency for perishable products. Journal of Cleaner Production, 242, 118428.
Amorim, P., & Almada-Lobo, B. (2014). The impact of food perishability issues in the vehicle routing problem. Computers & Industrial Engineering, 67, 223-233.
Amorim, P., Parragh, S. N., Sperandio, F., & Almada-Lobo, B. (2014). A rich vehicle routing problem dealing with perishable food: a case study. Top, 22(2), 489-508.
Barros, L., Linfati, R., & Escobar, J. W. (2020). An exact approach for the consistent vehicle routing problem (ConVRP). Advances in Production Engineering & Management, 15(3), 255-266.
Belo-Filho, M. A. F., Amorim, P., & Almada-Lobo, B. (2015). An adaptive large neighbourhood search for the operational integrated production and distribution problem of perishable products. International Journal of Production Research, 53(20), 6040-6058.
Bernal, J., Escobar, J. W., & Linfati, R. (2017). A granular tabu search algorithm for a real case study of a vehicle routing problem with a heterogeneous fleet and time windows. Journal of Industrial Engineering and Management, 10(4), 646-662.
Bernal-Moyano, J. A., Escobar, J. W., Marín-Moreno, C., Linfati, R., & Gatica, G. (2017). A comparison of trajectory granular based algorithms for the location-routing problem with heterogeneous fleet (LRPH). Dyna, 84(200), 193-201.
Bernal, J., Escobar, J. W., Paz, J. C., Linfati, R., & Gatica, G. (2018). A probabilistic granular tabu search for the distance constrained capacitated vehicle routing problem. International Journal of Industrial and Systems Engineering, 29(4), 453-477.
Bocarejo, J. P. (2020). Congestion in Latin American Cities: Innovative Approaches for a Critical Issue.
Bolanos, R., Escobar, J., & Echeverri, M. (2018). A metaheuristic algorithm for the multi-depot vehicle routing problem with heterogeneous fleet. International Journal of Industrial Engineering Computations, 9(4), 461-478.
Chávez, J., Escobar, J., Echeverri, M., & Meneses, C. (2018). A heuristic algorithm based on tabu search for vehicle routing problems with backhauls. Decision Science Letters, 7(2), 171-180.
Chen, H. K., Hsueh, C. F., & Chang, M. S. (2009). Production scheduling and vehicle routing with time windows for perishable food products. Computers & operations research, 36(7), 2311-2319.
Chowmali, W., & Sukto, S. (2020). A novel two-phase approach for solving the multi-compartment vehicle routing problem with a heterogeneous fleet of vehicles: a case study on fuel delivery. Decision Science Letters, 9(1), 77-90.
Cordeau, J. F., Gendreau, M., & Laporte, G. (1997). A tabu search heuristic for periodic and multi‐depot vehicle routing problems. Networks: An International Journal, 30(2), 105-119.
Escobar, J. W., Bravo, J. J., & Vidal, C. J. (2012). Optimización de redes de distribución de productos de consumo masivo en condiciones de riesgo. In Proceedings of XXXIII Congreso Nacional de Estadística e Investigación Operativa (SEIO), Madrid, Spain.
Escobar, J.W., & Linfati, R. (2012). Un algoritmo metaheurístico basado en recocido simulado con espacio de búsqueda granular para el problema de localización y ruteo con restricciones de capacidad. Revista Ingenierías Universidad de Medellín, 11(21), 139-150.
Escobar, J.W., Linfati, R., & Toth, P. (2013). A two-phase hybrid heuristic algorithm for the capacitated location-routing problem. Computers & Operations Research, 40(1), 70–79.
Escobar, J.W., Linfati, R., Toth, P., & Baldoquin, M. G. (2014a). A hybrid granular tabu search algorithm for the multi-depot vehicle routing problem. Journal of heuristics, 20(5), 483–509.
Escobar, J. W., Linfati, R., Baldoquin, M. G., & Toth, P. (2014b). A Granular Variable Tabu Neighborhood Search for the capacitated location-routing problem. Transportation Research Part B: Methodological, 67, 344–356.
Escobar, J.W., Linfati, R., & Adarme-Jaimes, W. (2015a). A hybrid metaheuristic algorithm for the capacitated location routing problem. Dyna, 82(189), 243–251.
Escobar, J. W., Linfati, R., & Adarme Jaimes, W. (2015b). Problema de localización y ruteo con restricciones de capacidad: Revisión de la Literatura. Revista Facultad de Ingeniería, 24(39), 85-98
Escobar, J.W., Adarme-Jaimes, W., & Clavijo-Buriticá, N. (2017). Comparative analysis of granular neighborhoods in a Tabu Search for the vehicle routing problem with heterogeneous fleet and variable costs (HFVRP). Revista Facultad de Ingeniería, 26(46), 93-104.
Escobar-Falcón, L., Alvarez-Martinez, D., Wilmer-Escobar, J., & Granada-Echeverri, M. (2021). A specialized genetic algorithm for the fuel consumption heterogeneous fleet vehicle routing problem with bidimensional packing constraints. International Journal of Industrial Engineering Computations, 12(2), 191-204.
Esmaili, M., & Sahraeian, R. (2017). A new bi-objective model for a two-echelon capacitated vehicle routing problem for perishable products with the environmental factor. International Journal of Engineering, 30(4), 523-531.
Flamini, M., Nigro, M., & Pacciarelli, D. (2011). Assessing the value of information for retail distribution of perishable goods. European Transport Research Review, 3(2), 103-112.
Ganji, M., Kazemipoor, H., Molana, S. M. H., & Sajadi, S. M. (2020). A green multi-objective integrated scheduling of production and distribution with heterogeneous fleet vehicle routing and time windows. Journal of Cleaner Production, 259, 120824.
Ghannadpour, S. F., & Zarrabi, A. (2019). Multi-objective heterogeneous vehicle routing and scheduling problem with energy minimizing. Swarm and evolutionary computation, 44, 728-747.
Hanum, F., Hadi, M., Aman, A., & Bakhtiar, T. (2019). Vehicle routing problems in rice-for-the-poor distribution. Decision Science Letters, 8(3), 323-338.
Hashimoto, H., Ibaraki, T., Imahori, S., & Yagiura, M. (2006). The vehicle routing problem with flexible time windows and traveling times. Discrete Applied Mathematics, 154(16), 2271-2290.
Helsgaun, K. (2000). An effective implementation of the Lin–Kernighan traveling salesman heuristic. European Journal of Operational Research, 126(1), 106–130.
Hsu, C. I., Hung, S. F., & Li, H. C. (2007). Vehicle routing problem with time-windows for perishable food delivery. Journal of food engineering, 80(2), 465-475.
Jafari Nozar, F., & Behnamian, J. (2020). Hyper-heuristic for integrated due-window scheduling and vehicle routing problem for perishable products considering production quality. Engineering Optimization, 1-20.
Kang, H. Y., & Lee, A. H. (2018). An Enhanced Approach for the Multiple Vehicle Routing Problem with Heterogeneous Vehicles and a Soft Time Window. Symmetry, 10(11), 650.
Linfati, R., Escobar, J. W., & Gatica, G. (2014a). Un algoritmo metaheurístico para el problema de localización y ruteo con flota heterogénea. Ingeniería y Ciencia, 10(19), 55-76.
Linfati, R., Escobar, J. W., & Cuevas, B. (2014b). An algorithm based on granular tabu search for the problem of balancing public bikes by using multiple vehicles. Dyna, 81(186), 284-294.
Liu, G., Hu, J., Yang, Y., Xia, S., & Lim, M. K. (2020). Vehicle routing problem in cold Chain logistics: A joint distribution model with carbon trading mechanisms. Resources, Conservation and Recycling, 156, 104715.
Ma, Z. J., Wu, Y., & Dai, Y. (2017). A combined order selection and time-dependent vehicle routing problem with time widows for perishable product delivery. Computers & Industrial Engineering, 114, 101-113.
Molina, J. C., Salmeron, J. L., & Eguia, I. (2020a). An ACS-based memetic algorithm for the heterogeneous vehicle routing problem with time windows. Expert Systems with Applications, 157, 113379.
Molina, J. C., Salmeron, J. L., Eguia, I., & Racero, J. (2020b). The heterogeneous vehicle routing problem with time windows and a limited number of resources. Engineering Applications of Artificial Intelligence, 94, 103745.
Nagle, S. K., & Panneerselvam, R. (2018). Study of Crossover operators of Genetic Algorithm& Development of New Crossover Operator to Solve Heterogeneous Vehicle Routing Problem with Time Windows. International Journal of Production Technology and Management (IJPTM), 9(2).
Nosrati, M., & Khamseh, A. (2020). Bi objective hybrid vehicle routing problem with alternative paths and reliability. Decision Science Letters, 9(2), 145-162.
Osvald, A., & Stirn, L. Z. (2008). A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food. Journal of food engineering, 85(2), 285-295.
Paz, J., Orozco, J., Salinas, J., Buriticá, N., & Escobar, J. (2015). Redesign of a supply network by considering stochastic demand. International Journal of Industrial Engineering Computations, 6(4), 521-528.
Puenayán, D. E., Londoño, J. C., Escobar, J. W., & Linfati, R. (2014). Un algoritmo basado en búsqueda tabú granular para la solución de un problema de ruteo de vehículos considerando flota heterogénea. Revista Ingenierías Universidad de Medellín, 13(25), 81-98.
Qin, G., Tao, F., & Li, L. (2019). A vehicle routing optimization problem for cold chain logistics considering customer satisfaction and carbon emissions. International journal of environmental research and public health, 16(4), 576.
Rahbari, A., Nasiri, M. M., Werner, F., Musavi, M., & Jolai, F. (2019). The vehicle routing and scheduling problem with cross-docking for perishable products under uncertainty: Two robust bi-objective models. Applied Mathematical Modelling, 70, 605-625.
Rezaei, N., Ebrahimnejad, S., Moosavi, A., & Nikfarjam, A. (2019). A green vehicle routing problem with time windows considering the heterogeneous fleet of vehicles: two metaheuristic algorithms. European Journal of Industrial Engineering, 13(4), 507-535.
Ritchie, H., & Roser, M. (2020). Environmental impacts of food production. Our world in data.
Rodado, D., Escobar, J., García-Cáceres, R., & Atencio, F. (2017). A mathematical model for the product mixing and lot-sizing problem by considering stochastic demand. International Journal of Industrial Engineering Computations, 8(2), 237-250.
Sahraeian, R., & Esmaeili, M. (2018). A multi-objective two-echelon capacitated vehicle routing problem for perishable products. Journal of Industrial and Systems Engineering, 11(2), 62-84.
Schroeder, H., Boykoff, M. T., & Spiers, L. (2012). Equity and state representations in climate negotiations. Nature Climate Change, 2(12), 834-836.
Sepúlveda, J., Escobar, J. W., & Adarme-Jaimes, W. (2014). An algorithm for the routing problem with split deliveries and time windows (SDVRPTW) applied on retail SME distribution activities. Dyna, 81(187), 223-231.
Song, B. D., & Ko, Y. D. (2016). A vehicle routing problem of both refrigerated-and general-type vehicles for perishable food products delivery. Journal of food engineering, 169, 61-71.
Song, M. X., Li, J. Q., Han, Y. Q., Han, Y. Y., Liu, L. L., & Sun, Q. (2020). Metaheuristics for solving the vehicle routing problem with the time windows and energy consumption in cold chain logistics. Applied Soft Computing, 95, 106561.
Susilawati, E., Mawengkang, H., & Efendi, S. (2018). An integer programming model for solving heterogeneous vehicle routing problem with hard time window considering service choice. In IOP Conference Series: Materials Science and Engineering (Vol. 300, No. 1, p. 012023). IOP Publishing.
Taillard, É. D., Laporte, G., & Gendreau, M. (1996). Vehicle routing with multiple use of vehicles. Journal of the Operational research society, 47(8), 1065-1070.
Taniguchi, E., Thompson, E., Yamada, T., van Duin, J., & Logistics, C. (2001). Network Modelling and Intelligent Transport Systems, Pergamon, Oxford.
Tirkolaee, E. B., Hadian, S., Weber, G. W., & Mahdavi, I. (2020). A robust green traffic‐based routing problem for perishable products distribution. Computational Intelligence, 36(1), 80-101.
Toth, P., & Vigo, D. (2003). The granular tabu search and its application to the vehicle-routing problem. Informs Journal on computing, 15(4), 333–346.
Utama, D. M., Dewi, S. K., Wahid, A., & Santoso, I. (2020). The vehicle routing problem for perishable goods: A systematic review. Cogent Engineering, 7(1), 1816148.
Vélez, Y. S., Varela, H. P., Londoño, J. C., & Escobar, J. W. (2021). Redesign of supply chains for agricultural companies considering multiple scenarios by the methodology of sample average approximation. International Journal of Business Performance and Supply Chain Modelling, 12(1), 44-68.
Wang, Z., & Wen, P. (2020). Optimization of a low-carbon two-echelon heterogeneous-fleet vehicle routing for cold chain logistics under mixed time window. Sustainability, 12(5), 1967.
Wu, Y., Zheng, B., & Zhou, X. (2020). A Disruption Recovery Model for Time-Dependent Vehicle Routing Problem With Time Windows in Delivering Perishable Goods. IEEE Access, 8, 189614-189631.
Yu, Y., Wang, S., Wang, J., & Huang, M. (2019). A branch-and-price algorithm for the heterogeneous fleet green vehicle routing problem with time windows. Transportation Research Part B: Methodological, 122, 511-527.
Zulvia, F. E., Kuo, R. J., & Nugroho, D. Y. (2020). A many-objective gradient evolution algorithm for solving a green vehicle routing problem with time windows and time dependency for perishable products. Journal of Cleaner Production, 242, 118428.