scholarly journals Green and Reliable Freight Routing Problem in the Road-Rail Intermodal Transportation Network with Uncertain Parameters: A Fuzzy Goal Programming Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-21 ◽  
Author(s):  
Yan Sun
Keyword(s):  
Transportation Network ◽  
Mixed Integer ◽  
Programming Approach ◽  
Uncertain Parameters ◽  
Intermodal Transportation ◽  
Road Transportation ◽  
Routing Problem ◽  
The Road ◽  
Green Routing ◽  
Freight Routing

In this study, the author focuses on modeling and optimizing a freight routing problem in a road-rail intermodal transportation network that combines the hub-and-spoke and point-to-point structures. The operations of road transportation are time flexible, while rail transportation has fixed departure times. The reliability of the routing is improved by modeling the uncertainty of the road-rail intermodal transportation network. Parameters that are influenced by the real-time status of the network, including capacities, travel times, loading and unloading times, and container trains’ fixed departure times, are considered uncertain in the routing decision-making. Based on fuzzy set theory, triangular fuzzy numbers are employed to formulate the uncertain parameters as well as resulting uncertain variables. Green routing is also discussed by treating the minimization of carbon dioxide emissions as an objective. First of all, a multiobjective fuzzy mixed integer nonlinear programming model is established for the specific reliable and green routing problem. Then, defuzzification, linearization, and weighted sum method are implemented to present a crisp linear model whose global optimum solutions can be effectively obtained by the exact solution algorithm run by mathematical programming software. Finally, a numerical case is given to demonstrate how the proposed methods work. In the case, sensitivity analysis is adopted to reveal the effects of uncertainty on the routing optimization. Fuzzy simulation is then performed to help decision makers to select the best crisp route plan by determining the best confidence level shown in the fuzzy chance constraints.

scholarly journals Modeling the Multicommodity Multimodal Routing Problem with Schedule-Based Services and Carbon Dioxide Emission Costs

2015 ◽  
Vol 2015 ◽  
pp. 1-21 ◽  
Author(s):  
Yan Sun ◽  
Maoxiang Lang
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Transportation Network ◽  
Linearization Method ◽  
Mixed Integer ◽  
Multicommodity Flow ◽  
Routing Problem ◽  
Multimodal Transportation ◽  
Proposed Model ◽  
Freight Routing

We explore a freight routing problem wherein the aim is to assign optimal routes to move commodities through a multimodal transportation network. This problem belongs to the operational level of service network planning. The following formulation characteristics will be comprehensively considered: (1) multicommodity flow routing; (2) a capacitated multimodal transportation network with schedule-based rail services and time-flexible road services; (3) carbon dioxide emissions consideration; and (4) a generalized costs optimum oriented to customer demands. The specific planning of freight routing is thus defined as a capacitated time-sensitive multicommodity multimodal generalized shortest path problem. To solve this problem systematically, we first establish a node-arc-based mixed integer nonlinear programming model that combines the above formulation characteristics in a comprehensive manner. Then, we develop a linearization method to transform the proposed model into a linear one. Finally, a computational experiment from the Chinese inland container export business is presented to demonstrate the feasibility of the model and linearization method. The computational results indicate that implementing the proposed model and linearization method in the mathematical programming software Lingo can effectively solve the large-scale practical multicommodity multimodal transportation routing problem.

scholarly journals A Fuzzy Programming Method for Modeling Demand Uncertainty in the Capacitated Road–Rail Multimodal Routing Problem with Time Windows

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 91 ◽  
Author(s):  
Yan Sun ◽  
Xia Liang ◽  
Xinya Li ◽  
Chen Zhang
Keyword(s):  
Demand Uncertainty ◽  
Transportation Network ◽  
Time Windows ◽  
Mixed Integer ◽  
Credibility Measure ◽  
Chance Constrained Programming ◽  
Road Transportation ◽  
Routing Problem ◽  
Operational Level ◽  
Fuzzy Expected Value

Demand uncertainty is an important issue that influences the strategic, tactical, and operational-level decision making in the transportation/logistics/supply chain planning. In this study, we explore the effect of demand uncertainty on the operational-level freight routing problem in the capacitated multimodal transportation network that consists of schedule-based rail transportation and time-flexible road transportation. Considering the imprecise characteristic of the demand, we adopt fuzzy set theory to model its uncertainty and use trapezoidal fuzzy numbers to represent the fuzzy demands. We set multiple transportation orders as the optimization object and employ soft time windows to reflect the customer requirement on on-time transportation. Under the above situation, we establish a fuzzy mixed integer nonlinear programming (FMINLP) model to formulate the capacitated road–rail multimodal routing problem with demand uncertainty and time windows. We first use the fuzzy expected value model and credibility measure based fuzzy chance-constrained programming to realize the defuzziness of the model and then adopt linearization technique to reformulate the crisp model to finally generate an equivalent mixed integer linear programming (MILP) model that can be solved by standard mathematical programming software. Finally, a numerical case is presented to demonstrate the feasibility of the proposed method. Sensitivity analysis and fuzzy simulation are combined to quantify the effect of demand uncertainty on the routing problem and also reveal some helpful insights and managerial implications.

scholarly journals A Simulated Annealing Algorithm for Intermodal Transportation on Incomplete Networks

2021 ◽  
Vol 11 (10) ◽  
pp. 4467
Author(s):  
Mustapha Oudani
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Transportation Network ◽  
Sustainable Transportation ◽  
Mixed Integer ◽  
Intermodal Transportation ◽  
Efficient Design ◽  
Road Transportation ◽  
Mixed Integer Linear Program ◽  
Annealing Algorithm

Growing competition in the world enforces the need for an efficient design of transportation networks. Furthermore, a competitive transportation network should also be eco-friendly. As road transportation is responsible for the largest quantities of CO2 emissions, Intermodal Transportation (IT) might be a potential alternative. From this perspective, intermodal terminals location is a cornerstone for building a sustainable transportation network. The purpose of this paper is to study and efficiently solve the Intermodal Terminal Location Problem on incomplete networks. We model this problem as a mixed integer linear program and develop a simulated annealing algorithm to tackle medium and large instances. The computational results show that the obtained solutions using simulated annealing are competitive and close to the exact solutions found by CPLEX solver for small and medium instances. The same developed algorithm outperforms the best found solutions from the literature using heuristics for larger instances.

scholarly journals A New Heuristic Method for Transportation Network and Land Use Problem

2016 ◽  
Vol 8 (3) ◽  
pp. 94 ◽  
Author(s):  
Mouhamadou A.M.T. Bald ◽  
Babacar M. Ndiaye
Keyword(s):  
Land Use ◽  
Transportation Network ◽  
Heuristic Method ◽  
Optimization Techniques ◽  
Geographical Information ◽  
Mixed Integer ◽  
Individual Agent ◽  
The Road ◽  
Agent Simulation ◽  
Network Costs

Our paper deals with the Transportation Network and Land Use (TNLU) problem.  It consists in finding, simultaneously, the best location of urban area activities, as well as of the road network design that may minimize the moving cost in the network, and the network costs. We propose a new mixed integer programming formulation of the problem, and a new heuristic method for the resolution of TNLU. Then, we give a methodology to find locations or relocations of some Dakar region amenities (home, shop, work and leisure places), that may reduce travel time or travel distance. The proposed methodology mixes multi-agent simulation with combinatorial optimization techniques; that is individual agent strategies versus global optimization using Geographical Information System. Numerical results which show the effectiveness of the method,  and simulations based on the scenario of Dakar city are given.

Domiciling Truck Drivers More Strategically in a Transportation Network

2018 ◽  
pp. 846-865
Author(s):  
Kerry Melton ◽  
Sandeep Parepally
Keyword(s):  
Numerical Experiment ◽  
Transportation Network ◽  
Truck Drivers ◽  
Mixed Integer ◽  
Quadratic Program ◽  
Routing Problem ◽  
New Approach ◽  
Driving Time ◽  
Highway Transportation ◽  
Integer Quadratic Program

The authors propose a method to better domicile truck drivers in a relay-point highway transportation network to obtain better solutions for the truck driver domiciling and sourcing problem. The authors exploit characteristics of the truckload driver routing problem over a transportation network and introduce a new approach to domicile, source, and route truck drivers while more inclusively considering performance and cost measures related to the driver, transportation carrier, and customer. Driver domicile and relay-point locations are exploited to balance driver pay and recruiting costs and driving time. A mixed integer quadratic program will determine where driver domiciles are located to base drivers, source drivers, route drivers, etc. while considering key costs related to transporting truckload freight over long distances. A method to improve driver domicile locations is introduced to enhance driving jobs and driver sourcing, but not at the expense of the transportation carrier and customer. A numerical experiment will be conducted.

A Minimum Cost and Maximum Flow Model of Hazardous Materials Transportation

2011 ◽  
Vol 305 ◽  
pp. 363-366 ◽  
Author(s):  
Qing Ping Gao
Keyword(s):  
Transportation Network ◽  
Flow Distribution ◽  
Minimum Cost ◽  
Maximum Flow ◽  
Hazardous Materials ◽  
Social Risk ◽  
Routing Problem ◽  
Hazardous Materials Transportation ◽  
The Road ◽  
Road Section

A vehicle routing problem of hazardous materials transportation is studied in this paper. Firstly, the maximum permissible flow of the road section is calculated according to the social risk and accident rate values. Secondly, based on the structural measures and basic transportation network, the maximum permissible flow of the road section is taken as road section capacity, the minimum risk is taken as general minimum cost , and a minimum cost and maximum flow method is introduced to solve the flow distribution problem of hazardous materials transportation. Finally, the effectiveness of the method is illustrated with a simple numerical example.

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