Achillas, C., Moussiopoulos, N., Karagiannidis, A., Banias, G., and Perkoulidis, G. (2013). The use of multi-criteria decision analysis to tackle waste management problems: A literature review. Waste Management and Research, 31(2), 115-129. doi:doi:10.1177/0734242X12470203
Alçada-Almeida, L., Coutinho-Rodrigues, J., and Current, J. (2009). A multiobjective modeling approach to locating incinerators.
Socio-Economic Planning Sciences, 43(2), 111-120. doi:
http://dx.doi.org/10.1016/j.seps.2008.02.008
Ardjmand, E., Young, W. A., Weckman, G. R., Bajgiran, O. S., Aminipour, B., and Park, N. (2016). Applying genetic algorithm to a new bi-objective stochastic model for transportation, location, and allocation of hazardous materials. Expert Systems with Applications, 51, 49-58.
Caballero, R., González, M., Guerrero, F. M., Molina, J., and Paralera, C. (2007). Solving a multiobjective location routing problem with a metaheuristic based on tabu search. Application to a real case in Andalusia.
European Journal of Operational Research, 177(3), 1751-1763. doi:
http://dx.doi.org/10.1016/j.ejor.2005.10.017
Carotenuto, P., Giordani, S., and Ricciardelli, S. (2007). Finding minimum and equitable risk routes for hazmat shipments.
Computers and Operations Research, 34(5), 1304-1327. doi:
http://dx.doi.org/10.1016/j.cor.2005.06.003
Chiou, S.-W. (2017). A risk-averse signal setting policy for regulating hazardous material transportation under uncertain travel demand. Transportation Research Part D: Transport and Environment, 50, 446-472.
Dadkar, Y., Jones, D., and Nozick, L. (2008). Identifying geographically diverse routes for the transportation of hazardous materials.
Transportation Research Part E: Logistics and Transportation Review, 44(3), 333-349. doi:
http://dx.doi.org/10.1016/j.tre.2006.10.010
Diebold, F., and Bichler, M. (2017). Matching with indifferences: A comparison of algorithms in the context of course allocation.
European Journal of Operational Research, 260(1), 268-282. doi:
http://dx.doi.org/10.1016/j.ejor.2016.12.011
Dinler, E., and Güngör, Z. (2017). Planning decisions for recycling products containing hazardous and explosive substances: A fuzzy multi-objective model. Resources, Conservation and Recycling, 117, 93-101.
Drexl, M., and Schneider, M. (2015). A survey of variants and extensions of the location-routing problem. European Journal of Operational Research, 241(2), 283-308.
Emek, E., and Kara, B. Y. (2007). Hazardous waste management problem: The case for incineration. Computers and Operations Research, 34(5), 1424-1441. doi:http://dx.doi.org/10.1016/j.cor.2005.06.011
Erkut, E., and Verter, V. (1998). Modeling of Transport Risk for Hazardous Materials. Operations Research, 46(5), 625-642. doi:10.1287/opre.46.5.625
Fabiano, B., Currò, F., Palazzi, E., and Pastorino, R. (2002). A framework for risk assessment and decision-making strategies in dangerous good transportation
. Journal of Hazardous Materials, 93(1), 1-15. doi:
http://dx.doi.org/10.1016/S0304-3894(02)00034-1
Farrokhi-Asl, H., Tavakkoli-Moghaddam, R., Asgarian, B., and Sangari, E. (2017). Metaheuristics for a bi-objective location-routing-problem in waste collection management. Journal of Industrial and Production Engineering, 34(4), 239-252.
Govindan, K., Jafarian, A., Khodaverdi, R., and Devika, K. (2014). Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food. International Journal of Production Economics, 152, 9-28.
Hong, J., Han, X., Chen, Y., Wang, M., Ye, L., Qi, C., and Li, X. (2017). Life cycle environmental assessment of industrial hazardous waste incineration and landfilling in China. The International Journal of Life Cycle Assessment, 22(7), 1054-1064.
Hu, T.-L., Sheu, J.-B., and Huang, K.-H. (2002). A reverse logistics cost minimization model for the treatment of hazardous wastes.
Transportation Research Part E: Logistics and Transportation Review, 38(6), 457-473. doi:
http://dx.doi.org/10.1016/S1366-5545(02)00020-0
Mavrotas, G. (2009). Effective implementation of the ε-constraint method in Multi-Objective Mathematical Programming problems.
Applied Mathematics and Computation, 213(2), 455-465. doi:
http://dx.doi.org/10.1016/j.amc.2009.03.037
Mehrjerdi, Y. Z., and Nadizadeh, A. (2013). Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands. European Journal of Operational Research, 229(1), 75-84.
Pamučar, D., Ljubojević, S., Kostadinović, D., and Đorović, B. (2016). Cost and risk aggregation in multi-objective route planning for hazardous materials transportation—a neuro-fuzzy and artificial bee colony approach.
Expert Systems with Applications, 65, 1-15. doi:
http://dx.doi.org/10.1016/j.eswa.2016.08.024
Pradhananga, R., Taniguchi, E., Yamada, T., and Qureshi, A. G. (2014). Environmental Analysis of Pareto Optimal Routes in Hazardous Material Transportation.
Procedia - Social and Behavioral Sciences, 125, 506-517. doi:
http://dx.doi.org/10.1016/j.sbspro.2014.01.1492
Rabbani, M., Farrokhi-Asl, H., and Asgarian, B. (2016). Solving a bi-objective location routing problem by a NSGA-II combined with clustering approach: Application in waste collection problem. Journal of Industrial Engineering International, 13(1), 13-27.
Rakas, J., Teodorović, D., and Kim, T. (2004). Multi-objective modeling for determining location of undesirable facilities.
Transportation Research Part D: Transport and Environment, 9(2), 125-138. doi:
http://dx.doi.org/10.1016/j.trd.2003.09.002
Rath, S., and Gutjahr, W. J. (2014). A math-heuristic for the warehouse location–routing problem in disaster relief. Computers and Operations Research, 42, 25-39.
ReVelle, C., Cohon, J., and Shobrys, D. (1991). Simultaneous siting and routing in the disposal of hazardous wastes. Transportation Science, 25(2), 138-145.
Saat, M. R., Werth, C. J., Schaeffer, D., Yoon, H., and Barkan, C. P. L. (2014). Environmental risk analysis of hazardous material rail transportation.
Journal of Hazardous Materials, 264, 560-569. doi:
http://dx.doi.org/10.1016/j.jhazmat.2013.10.051
Samanlioglu, F. (2013). A multi-objective mathematical model for the industrial hazardous waste location-routing problem.
European Journal of Operational Research, 226(2), 332-340. doi:
http://dx.doi.org/10.1016/j.ejor.2012.11.019
Saxena, G., Chandra, R., and Bharagava, R. N. (2016). Environmental Pollution, Toxicity Profile and Treatment Approaches for Tannery Wastewater and Its Chemical Pollutants.
Vidović, M., Ratković, B., Bjelić, N., and Popović, D. (2016). A two-echelon location-routing model for designing recycling logistics networks with profit: MILP and heuristic approach. Expert Systems with Applications, 51, 34-48.
Wang, Z., Yin, J., and Ma, W. (2008, 1-6 June 2008). A reverse logistics optimization model for hazardous waste in the perspective of fuzzy multi-objective programming theory. Paper presented at the 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).
Xie, Y., Lu, W., Wang, W., and Quadrifoglio, L. (2012). A multimodal location and routing model for hazardous materials transportation. Journal of hazardous materials, 227, 135-141.
Xu, T., Yang, F., Li, J., and Yuan, W. (2013). A bi-objective mathematical model for hazmat vehicle routing problem with path-based risk estimation. Paper presented at the Business Intelligence and Financial Engineering (BIFE), 2013 Sixth International Conference on.
Yilmaz, O., Kara, B. Y., and Yetis, U. (2017). Hazardous waste management system design under population and environmental impact considerations. Journal of Environmental Management. 203, 720-731.
Zhang, D., Cai, S., Ye, F., Si, Y. W., and Nguyen, T. T. (2017). A hybrid algorithm for a vehicle routing problem with realistic constraints. Information Sciences, 394, 167-182.