Road network pricing and design for ordinary and hazmat vehicles: Integrated model and specialized local search

López-Ramos, Francisco; Nasini, Stefano; Guarnaschelli, Armando

doi:10.1016/j.cor.2019.05.006

Cited by 12 publications

(6 citation statements)

References 33 publications

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“…Our problem is considered as a transportation network design problem. Its mathematical programming formulation generally relates to regulatory policies on shipments with hazmat, aiming at minimizing the total network risk [12].…”

Section: Hazmat Transportationmentioning

confidence: 99%

“…Wang [19] introduced the speed limit strategy for hazmat transportation. López-Ramos et al [12] presented an integrated model and specialized local search for the road network pricing and the design of hazmat vehicles.…”

Section: Hazmat Transportationmentioning

confidence: 99%

“…is paper is the modelling integration of hazmat transportation problem and network design problem from policy integration perspective. at can be interpreted as an expansion of the policy integration proposed by [12] considering the exclusive right-ofway of hazmat vehicles. Additionally, there is still dearth of efficient heuristic algorithms for large-scale problems [6].…”

Section: Introductionmentioning

confidence: 99%

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Bilevel Optimization for the Hazmat Transportation Problem with Lane Reservation

Zhang

Hui

Bai

et al. 2020

Journal of Advanced Transportation

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In this study, we investigate a bilevel optimization model for the hazmat transportation problem with lane reservation. The problem lies in selecting lanes to be reserved in the network and planning paths for hazmat transportation tasks. The trade-off among transportation cost, risk, and impact on the normal traffic is considered. By using the traffic flow theory, we quantify the impact on the normal traffic and modify the traditional risk measurement model. The problem is formulated as a multiobjective bilevel programming model involving the selection of reserved lanes for government and planning paths for hazmat carriers. Two hybrid metaheuristic algorithms based on the particle swarm optimization algorithm and the genetic algorithm, respectively, are proposed to solve the bilevel model. Their performance on small-scale instances is compared with exact solutions based on the enumeration method. Finally, the computational results on large-scale instances are compared and sensitivity analysis on the key parameters is presented. The results indicate the following: (1) Both algorithms are effective methods for solving this problem, and the method based on the particle swarm optimization algorithm requires a shorter computation time, whereas the method based on the genetic algorithm shows more advantages in optimality. (2) The bilevel model can effectively reduce the total risk of the hazmat transportation while considering the interests of hazmat carriers and ordinary travellers. (3) The utilization rate of reserved lanes increases with an increasing number of tasks. Nevertheless, once the proportion of hazmat vehicles becomes excessive, the advantage of reducing the risk of the reserved lanes gradually decreases.

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Section: Hazmat Transportationmentioning

confidence: 99%

Section: Hazmat Transportationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Bilevel Optimization for the Hazmat Transportation Problem with Lane Reservation

Zhang

Hui

Bai

et al. 2020

Journal of Advanced Transportation

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“…In most cases, heuristic algorithms are only able to solve the small-sized problems whereas most practical applications usually involve a large number of customers. Hence, some researchers tried to use the meta-heuristic algorithms in their studies [20,[25][26][27][28][29]. As one, the presented three-objective mathematical model by Jalili Ball et al [30] minimizes the total costs (cost of transportation and cost of delay) and total risks due to the time window limitation and the environmental factors to restore the balance of the allocated route to each vehicle.…”

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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“…Ghaderi and Robert [23] proposed an integrated location and routing approach for transporting hazardous materials in a bimodal transportation network. López-Ramos et al [24] presented an integrated model and specialized local search for the road network pricing and the design of hazmat vehicles. In addition, Feng Chen et al [25][26][27] analyzed the accidents involving drivers that transported goods under bad driving conditions.…”

Section: Introductionmentioning

confidence: 99%

Design of a Network Optimization Platform for the Multivehicle Transportation of Hazardous Materials

Dong

Zhou

2020

IJERPH

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With economic development, the volume of hazardous materials is increasing, and the potential risks to human beings and the natural environment are expanding. Road transportation has become the main mode of transportation for hazardous materials. Because of the specific characteristics of hazardous materials, if an accident occurs in the transportation process, it often causes mass casualties, serious property and socioeconomic damage, and damage to the ecological environment. Hence, transportation is an important part of the life cycle of hazardous materials. This paper designs an optimization platform for multidestination, multiterminal, and multivehicle networks that transport hazardous materials. The logistics module in TransCAD software is used to construct this platform. By identifying the effective transportation routes considering the transportation risk, sensitive target population, and transportation time of each road section, the entropy method can be used to fuse and obtain the comprehensive impedance value of each road section. Finally, the optimal transportation network of hazardous materials was obtained by the transportation network optimization algorithm in TransCAD. The platform can display the optimal transport program with data windows, text, and maps. The research results provide a reference for relevant departments to scientifically manage the transport of hazardous materials.

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Road network pricing and design for ordinary and hazmat vehicles: Integrated model and specialized local search

Cited by 12 publications

References 33 publications

Bilevel Optimization for the Hazmat Transportation Problem with Lane Reservation

Bilevel Optimization for the Hazmat Transportation Problem with Lane Reservation

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

Design of a Network Optimization Platform for the Multivehicle Transportation of Hazardous Materials

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