Planning and managing intermodal transportation of hazardous materials with capacity selection and congestion

Assadipour, Ghazal; Ke, Ginger Y.; Verma, Manish

doi:10.1016/j.tre.2015.02.003

Cited by 67 publications

(30 citation statements)

References 18 publications

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“…Current research indicates that operational and tactical decisions are interrelated. Operational intermodal routing problems may include real-time planning and replanning [11,14,[16][17][18] and asset management (and repositioning) decisions [11,16,[19][20][21]. They sometimes include fixed costs for selecting services, which relates to the tactical service network design.…”

Section: Long-haul Service Network Design and Intermodal Routingmentioning

confidence: 99%

“…Tactical problems usually assume that delivery time windows can be violated, whereas at the operational phase, time windows are usually constraints. However, some operational problems allow late delivery at a penalty cost [14,17,20,22]. This shows that different decision levels are linked.…”

Section: Long-haul Service Network Design and Intermodal Routingmentioning

confidence: 99%

“…Time windows at each node must be respected (17)- (19). Constraints (20) set the time variables between subsequent nodes. Constraints (21)-(26) represent three pairs of constraints of which either one or the other must hold, depending on whether a service in a node is executed at any time or day before or after spending a particular night at that node.…”

Section: Vehicle Routing Problem In Each Regionmentioning

confidence: 99%

“…The acceptance criterion for moves includes a function with multiple cost components (lines [18][19][20]. The total costs of each solution consist of vehicle routing costs in both service regions (sol new .vrpCost), two-way direct truck costs for drayage tasks to be executed in the next planning period as a result of long-haul services with arrival in the next week (sol new .directTruckCost), and long-haul transport costs (sol new .railCost).…”

Section: General Structure Of the Lnsmentioning

confidence: 99%

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Intermodal Container Routing: Integrating Long-Haul Routing and Local Drayage Decisions

et al. 2019

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Intermodal logistics service providers decide on the routing of demand through their service network. Long-haul routing decisions determine the selected departure and arrival terminals for containers and imply corresponding drayage tasks. Traditionally, given these long-haul routes and fixed drayage tasks, drayage operations are planned in a second phase by establishing truck routes to transport containers to and from terminals by truck. In this paper, operational decisions on local drayage routing in large-volume freight regions with multiple terminals on the one hand, and intermodal long-haul routing on the other hand are merged into an integrated intermodal routing problem. Different long-haul routing decisions imply different drayage tasks to be performed and thus impact total trucking costs. The approach aims at reducing the number of road kilometres and increases bundling opportunities by maximising the long-haul capacity utilisation. In this way, it contributes to the modal shift towards intermodal transport and a more sustainable transport system. As a weekly planning horizon is used, a maximum daily active time and a minimum overnight's rest are included for multi-day drayage routing. A large neighbourhood search heuristic is proposed to solve the integrated intermodal routing problem. This integrated planning approach provides decision support for routing customer orders throughout the intermodal network with the aim of minimising total transport costs and maximising capacity utilisation. Experiments show the added value of the integrated approach, which uses more information to make better-informed decisions and increase the capacity utilisation. The largest savings in trucking costs are obtained for clustered instances with demand characteristics closest to real-life cases. Finally, a real-life case study analyses the impact of tactical service network design decisions on the total operational costs.

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Section: Long-haul Service Network Design and Intermodal Routingmentioning

confidence: 99%

Section: Long-haul Service Network Design and Intermodal Routingmentioning

confidence: 99%

Section: Vehicle Routing Problem In Each Regionmentioning

confidence: 99%

Section: General Structure Of the Lnsmentioning

confidence: 99%

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Intermodal Container Routing: Integrating Long-Haul Routing and Local Drayage Decisions

et al. 2019

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“…Fan et al [8] formulated a bi-objective programming model that minimizes risk and cost for urban hazardous materials transportation, with consideration of road closure due to traffic controls, weather conditions, curfew and construction activities. Assadipour et al [9] proposed a bi-objective optimization framework that considers both cost and risk for the rail-truck intermodal transportation of hazardous materials with terminal congestion.…”

Section: Introductionmentioning

confidence: 99%

Multi-period hazardous waste collection planning with consideration of risk stability

Ma¹,

Li²

2021

Journal of Industrial &Amp; Management Optimization

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Hazardous wastes are likely to cause danger to humans and the environment. In this paper, a new mathematical optimization model is developed for the multi-period hazardous waste collection planning problem. The hazardous wastes generated by each source are time-varying in weight and allow incomplete and delayed collection. The aim of the model is to help decision makers determine the weight of hazardous wastes to collect from each source and the transportation routes of vehicles in each period. In the developed model, three objectives are considered simultaneously: (1) minimisation of total cost over all periods, which includes start-up fee of vehicles, transportation cost of hazardous wastes, and penalty fee for the delayed collection; (2) minimisation of total transportation risk posing to the surrounding of routes over all periods; and (3) even distribution of transportation risk among all periods, also called risk stability. The developed multi-objective model is transformed into a single-objective one based on the weighted sums method, which is finally equated to a mixed 0-1 linear programming by introducing a set of auxiliary variables and constraints. Numerical experiments are computed with CPLEX software to find the optimal solutions. The computational results and parameters analysis demonstrate the applicability and validity of the developed model. It is found that the consideration of the risk stability can reduce the total transportation risk, the uneven distribution of the transportation risk among all periods, and the maximum number of vehicles used, though increasing the total cost to some extent.2010 Mathematics Subject Classification. Primary: 90B06, 90B50; Secondary: 90C30.

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Discrete Event Simulation of Loading Unloading Operations in a Specific Intermodal Transportation Context

Fatnassi

Chaouachi²

2016

Advances in Intelligent Systems and Computing

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Planning and managing intermodal transportation of hazardous materials with capacity selection and congestion

Cited by 67 publications

References 18 publications

Intermodal Container Routing: Integrating Long-Haul Routing and Local Drayage Decisions

Intermodal Container Routing: Integrating Long-Haul Routing and Local Drayage Decisions

Multi-period hazardous waste collection planning with consideration of risk stability

Discrete Event Simulation of Loading Unloading Operations in a Specific Intermodal Transportation Context

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