Hazardous materials collection with multiple-product loading

Paredes-Belmar, Germán; Bronfman, Andrés; Marianov, Vladimir; Latorre-Núñez, Guillermo

doi:10.1016/j.jclepro.2016.09.163

Cited by 24 publications

(9 citation statements)

References 26 publications

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“…The second group of models focuses on short-term decisions, i.e., routing and allocation. For instance, Paredes-Belmar et al. (2017) formulated an ILP for minimizing the cost of hazardous waste collection problem, where only the routing decisions were considered.…”

Section: Literature Reviewmentioning

confidence: 99%

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A stochastic network design problem for hazardous waste management

Sun

Solvang

et al. 2020

Journal of Cleaner Production

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Hazardous waste management is of paramount importance due to the potential threats posed to the environment and local residents. The design of a hazardous waste management system involves several important decisions, i.e., the determination of the locations and sizes of treatment, recycling and disposal facilities, and organizing the transportation of hazardous waste among different facilities. In this paper, we proposed a novel stochastic bi-objective mixed integer linear program (MILP) to support these decisions in order to reduce the population exposure to risk while simultaneously maintaining a high cost efficiency of the transportation and treatment of hazardous waste. Moreover, considering the inherent uncertainty within the planning horizon, the cost, demand and affected population are defined as stochastic parameters. A sample average approximation based goal programming (SAA-GP) approach is used to solve the mathematical model. The proposed model and solution method are validated through numerical experiments whose results show that uncertainty may not only affect the objective value but also lead to different strategic decisions in the network design of a hazardous waste management system. In this regard, the strategic decisions obtained by the stochastic model is more robust to the change of external environment. Finally, the model is applied in a real-world case study of healthcare waste management in Wuhan, China, in order to show its applicability.

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Section: Literature Reviewmentioning

confidence: 99%

“…(2017) × × × × × × Case study Farrokhi-Asl et al. (2017) × × × × × × Numerical experiment Paredes-Belmar et al. (2017) × × × × × Case study Yilmaz et al.…”

Section: Literature Reviewmentioning

confidence: 99%

A stochastic network design problem for hazardous waste management

Sun

Solvang

et al. 2020

Journal of Cleaner Production

View full text Add to dashboard Cite

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“…Various studies have been recommended Exact approaches to solve the VRPT problem, [11,12,[18][19][20]. Also, As VRPT is a Np-Hard problem with the complicated calculation, many studies have focused on the heuristic algorithms [9,[21][22][23]. As one, Zografos et al [24] investigated the VRPTW of HAZMAT transportation by proposing a bi-objective model and the weighting method is applied to convert the model into single-objective one.…”

Section: Literature Reviewmentioning

confidence: 99%

A novel fuzzy bi-objective vehicle routing and scheduling problem with time window constraint for a distribution system: A case study

et al. 2020

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In the process of hazardous material transportation, the risk is a significant factor that should be considered due to the potential severe consequence of an incident. Regardless of risks, time is a paramount concern that should be considered in hazardous material transportation. In this way, this paper introduces a bi-objective model for a vehicle routing and scheduling problem of hazardous material distribution problems under the fuzzy condition to minimize both total distribution time and risks. In the proposed model, the fuzzy inference system and fuzzy failure mode and effects analysis are applied to identify and calculate the high-level risks instead of the previous simple methods for the first time. Moreover, Jimenez method and fuzzy goal programming are respectively utilized to convert the fuzzy bi-objective model into the same crisp and single-objective one. Besides, to cope with the NP-hardness of the largesized problems, two meta-heuristic algorithms namely invasive weeds optimization and genetic algorithm is used, and several sensitivity analyses are performed to prove the efficiency of the proposed approach. The performance of the proposed algorithms is also assessed through a comparative study. Finally, the proposed model is implemented to a real case study to prove the validity of the model.

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“…Finally, they could achieve high benefits by implementing their suggested methodology in both cities. After them, many researchers have worked on VRPs and location-routing problems for USWM considering different characteristics such as hazardous waste and multiple waste products (Aydemir-Karadag, 2018;Hauge et al, 2014;Louati, 2016;Paredes-Belmar et al, 2017;Rabbani et al, 2018;Ramos et al, 2018;Tung and Pinnoi, 2000;Yilmaz et al, 2014). Furthermore, the VRP has been studied widely in the literature for various real-world applications (Mirmohammadi et al, 2017;Tirkolaee et al, 2017Tirkolaee et al, , 2019, but CARP has been almost neglected despite its effective practical aspects, particularly in USWM (Tirkolaee et al, 2018a).…”

Section: Literature Reviewmentioning

confidence: 99%

A hybrid augmented ant colony optimization for the multi-trip capacitated arc routing problem under fuzzy demands for urban solid waste management

et al. 2019

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Nowadays, urban solid waste management is one of the most crucial activities in municipalities and their affiliated organizations. It includes the processes of collection, transportation and disposal. These major operations require a large amount of resources and investments, which will always be subject to limitations. In this paper, a chance-constrained programming model based on fuzzy credibility theory is proposed for the multi-trip capacitated arc routing problem to cope with the uncertain nature of waste amount generated in urban areas with the aim of total cost minimization. To deal with the complexity of the problem and solve it efficiently, a hybrid augmented ant colony optimization algorithm is developed based on an improved max–min ant system with an innovative probability function and a simulated annealing algorithm. The performance of hybrid augmented ant colony optimization is enhanced by using the Taguchi parameter design method to adjust the parameters’ values optimally. The overall efficiency of the algorithm is evaluated against other similar algorithms using well-known benchmarks. Finally, the applicability of the suggested methodology is tested on a real case study with a sensitivity analysis to evolve the managerial insights and decision aids.

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Hazardous materials collection with multiple-product loading

Cited by 24 publications

References 26 publications

A stochastic network design problem for hazardous waste management

A stochastic network design problem for hazardous waste management

A novel fuzzy bi-objective vehicle routing and scheduling problem with time window constraint for a distribution system: A case study

A hybrid augmented ant colony optimization for the multi-trip capacitated arc routing problem under fuzzy demands for urban solid waste management

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