scholarly journals A Bi-Objective Fuzzy Credibilistic Chance-Constrained Programming Approach for the Hazardous Materials Road-Rail Multimodal Routing Problem under Uncertainty and Sustainability

2019 ◽  
Vol 11 (9) ◽  
pp. 2577 ◽  
Author(s):  
Yan Sun ◽  
Xinya Li ◽  
Xia Liang ◽  
Cevin Zhang
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emission ◽  
Hazardous Materials ◽  
Mixed Integer ◽  
Programming Approach ◽  
Population Exposure ◽  
Chance Constrained Programming ◽  
Routing Problem ◽  
Multimodal Transportation ◽  
Conflicting Objectives

Hazardous materials transportation involves extensive risk and cannot be avoided in practice. An advanced routing, however, can help to reduce the risk by planning the best transportation routes for hazardous materials that can make effective tradeoffs between the risk objective and the economic objective. In this study, we explore the hazardous materials routing problem in the road-rail multimodal transportation network with a hub-and-spoke structure, in which the risk is measured by the multiplication of population exposure and the associated volume of hazardous materials, and minimizing the total risk of all the transportation orders of hazardous materials is set as the risk objective. It is difficult to estimate the population exposure exactly during the routing decision-making process, which results in its uncertainty. In this study, we formulate the uncertain population exposure from a fuzzy programming perspective by using triangular fuzzy numbers. Moreover, the carbon dioxide emission constraint is formulated to realize the sustainable transportation of hazardous materials. To optimize the problem under the above framework, we first establish a bi-objective fuzzy mixed integer nonlinear programming model, and then develop a three-stage exact solution strategy that the combines fuzzy credibilistic chance constraint, linearization technique, and the normalized weighting method. Finally, a computational experiment is carried out to verify the feasibility of the proposed method in dealing with the problem. The experimental results indicate that tradeoffs between the two conflicting objectives can be effectively made by using the Pareto frontier to the hazardous materials routing problem. Furthermore, the credibility level and carbon dioxide emission cap significantly influence the hazardous materials routing optimization. Their effects on the optimization result are quantified by using sensitivity analysis, which can draw some useful insights to help decision makers to better organize the hazardous materials road-rail multimodal transportation under uncertainty and sustainability.

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 Green road–rail intermodal routing problem with improved pickup and delivery services integrating truck departure time planning under uncertainty: an interactive fuzzy programming approach

2021 ◽  
Author(s):  
Yan Sun ◽  
Nan Yu ◽  
Baoliang Huang
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emission ◽  
Fuzzy Programming ◽  
Programming Approach ◽  
Pickup And Delivery ◽  
Routing Problem ◽  
Service Levels ◽  
Departure Time ◽  
Delivery Services ◽  
Time Planning

AbstractThis paper addresses the multi-objective optimization for the road–rail intermodal routing problem that aims to minimize the total costs and carbon dioxide emissions of the routes. To achieve high timeliness of the entire transportation process, pickup and delivery services are simultaneously improved based on the employment of fuzzy soft time windows to measure their service levels. The modeling of road–rail intermodal routing considers fixed schedules of rail and time flexibility of road to match the real-world transportation scenario, in which travel times and carbon dioxide emission factors of road services are considered to be time-varying. To improve the feasibility of the routing, uncertainty of travel times and carbon dioxide emission factors of road services and capacities of rail services are incorporated into the problem. By applying trapezoidal fuzzy numbers to formulate the uncertainty, we propose a fuzzy multi-objective nonlinear optimization model for the routing problem that integrates the truck departure time planning for road services. After processing the model with fuzzy chance-constrained programming and linearization, we obtain an auxiliary equivalent crisp linear model and solve it by designing an interactive fuzzy programming approach with the Bounded Objective Function method. Based on an empirical case study, we demonstrate the validity of the proposed approach and discuss the effects of improving the confidence levels and service levels on the optimization results. The case analysis reveals several managerial insights that help to realize an efficient transportation organization by making effective trade-offs among lowering costs, reducing emissions, improving service levels, and enhancing feasibility.

scholarly journals Multidepot Heterogeneous Vehicle Routing Problem for a Variety of Hazardous Materials with Risk Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Bochen Wang ◽  
Qiyuan Qian ◽  
Zheyi Tan ◽  
Peng Zhang ◽  
Aizhi Wu ◽  
...  
Keyword(s):  
Risk Analysis ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Large Scale ◽  
Programming Model ◽  
Hazardous Materials ◽  
Mixed Integer ◽  
Small Scale ◽  
Routing Problem ◽  
Heterogeneous Vehicle Routing Problem

This study investigates a multidepot heterogeneous vehicle routing problem for a variety of hazardous materials with risk analysis, which is a practical problem in the actual industrial field. The objective of the problem is to design a series of routes that minimize the total cost composed of transportation cost, risk cost, and overtime work cost. Comprehensive consideration of factors such as transportation costs, multiple depots, heterogeneous vehicles, risks, and multiple accident scenarios is involved in our study. The problem is defined as a mixed integer programming model. A bidirectional tuning heuristic algorithm and particle swarm optimization algorithm are developed to solve the problem of different scales of instances. Computational results are competitive such that our algorithm can obtain effective results in small-scale instances and show great efficiency in large-scale instances with 70 customers, 30 vehicles, and 3 types of hazardous materials.

scholarly journals Synthesis of Sustainable Carbon Negative Eco-Industrial Parks

2021 ◽  
Vol 9 ◽  
Author(s):  
Elizabeth J. Abraham ◽  
Farah Ramadan ◽  
Dhabia M. Al-Mohannadi
Keyword(s):  
Carbon Dioxide ◽  
Circular Economy ◽  
Carbon Dioxide Emissions ◽  
Carbon Capture ◽  
Carbon Dioxide Emission ◽  
Value Added ◽  
Mixed Integer ◽  
Industrial Parks ◽  
And Storage

Growing climate change concerns in recent years have led to an increased need for carbon dioxide emission reduction. This can be achieved by implementing the concept of circular economy, which promotes the practice of resource conservation, emission minimization, and the maintenance of sustainable revenue streams. A considerable amount of carbon dioxide emissions is a consequence of stationary sources from industrial processes. These emissions can be reduced using carbon capture utilization and storage (CCUS) or reduced at source by using emission free renewable resources. The method developed within this work uses mixed integer linear programming (MILP) to design sustainable clusters that convert seawater (including waste brine), air, and waste carbon dioxide emissions to value-added products with sunlight as the main energy source. In this way, circular economy is employed to minimize fresh resource consumption and maximize material reuse. The potential of this work is demonstrated through a case study, which shows that an industrial park may be profitable while adhering to strict emission and material constraints.

scholarly journals Hazardous Materials Transportation with Multiple Objectives: A Case Study in Taiwan

2016 ◽  
Author(s):  
Ta-Yin Hu ◽  
Ya-Han Chang
Keyword(s):  
Hazardous Materials ◽  
Multiple Objectives ◽  
Compromise Programming ◽  
Programming Approach ◽  
Risk Indicator ◽  
Compromise Solution ◽  
Hazardous Material ◽  
Conflicting Objectives ◽  
Hazmat Transportation ◽  
Kaohsiung City

Hazardous material (hazmat) transportation has been an important issue for handling hazardous materials, such as gases and chemical liquids. In the past, researchers have made great efforts to develop policies and route planning methods for hazmat transportation problems. In 2014, Kaohsiung City in Taiwan suffered a gas pipeline explosion at midnight; 32 people were killed, and hundreds of people were injured. After the incident, policies and routing strategies for hazardous materials (hazmat) transportation in Kaohsiung were initiated to avoid pipeline transportation. Although methodologies for hazmat transportation have been proposed and implemented to minimize potential risks, multiple objectives need to be considered in the process to facilitate hazmat transportation in Taiwan. In order to consider both government and operators’ aspects, a multi-objective formulation for the hazmat problem is proposed and a compromise programming method is applied to solve the problem with two objectives: travel cost and risk. The path risk is defined based on risk assessment indexes, such as road characteristics, population distribution, link length, hazardous material characteristics, and accident rates. An aggregate risk indicator is proposed for roadway segments. The compromise programming approach is developed from the concept of compromise decision and the main idea is to search the compromise solution closest to the ideal solution. The proposed method is applied to Kaohsiung City, Taiwan. The results show that two conflicting objectives keep making trade-offs between each other until they finally reach a compromise solution.

Multiobjective Optimization for Hazardous Materials Transportation

2005 ◽  
Vol 1906 (1) ◽  
pp. 64-73 ◽  
Author(s):  
Bo Huang ◽  
Pierre Fery ◽  
Liangpei Zhang
Keyword(s):  
Hazardous Materials ◽  
Efficient Solutions ◽  
Geographical Information ◽  
Population Exposure ◽  
Hazardous Materials Transportation ◽  
Shortest Path Problems ◽  
Trade Offs ◽  
Conflicting Objectives

This research attempted to build a framework for determining optimal routes for hazardous materials transportation. Previous work has suggested the incorporation of many conflicting objectives in the analysis, such as travel cost, population exposure, environmental risk, and security concerns. Multiplying the number of objectives leads to complex shortest path problems that often have several efficient solutions. The present study emphasizes an overview of possible trade-offs among routes without generating all of them. A simple characterization of the efficient routes is used to select the best ones with no need for input from the decision maker. A case study with eight objective functions was performed on a road network in Singapore. A geographical information system was used to quantify road link attributes, which are assumed linear and deterministic for the sake of simplicity. The proposed algorithm derives four significantly different routes, which conform to intuition.

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 A Mathematical Model for the Industrial Hazardous Waste Location-Routing Problem

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Omid Boyer ◽  
Tang Sai Hong ◽  
Ali Pedram ◽  
Rosnah Bt Mohd Yusuff ◽  
Norzima Zulkifli
Keyword(s):  
Hazardous Waste ◽  
Cost Minimization ◽  
Human Life ◽  
Transportation Cost ◽  
Mixed Integer ◽  
Population Exposure ◽  
Routing Problem ◽  
Transportation Risk ◽  
Weighted Sum Method ◽  
Location Routing

Technology progress is a cause of industrial hazardous wastes increasing in the whole world . Management of hazardous waste is a significant issue due to the imposed risk on environment and human life. This risk can be a result of location of undesirable facilities and also routing hazardous waste. In this paper a biobjective mixed integer programing model for location-routing industrial hazardous waste with two objectives is developed. First objective is total cost minimization including transportation cost, operation cost, initial investment cost, and cost saving from selling recycled waste. Second objective is minimization of transportation risk. Risk of population exposure within bandwidth along route is used to measure transportation risk. This model can help decision makers to locate treatment, recycling, and disposal centers simultaneously and also to route waste between these facilities considering risk and cost criteria. The results of the solved problem prove conflict between two objectives. Hence, it is possible to decrease the cost value by marginally increasing the transportation risk value and vice versa. A weighted sum method is utilized to combine two objectives function into one objective function. To solve the problem GAMS software with CPLEX solver is used. The problem is applied in Markazi province in Iran.

scholarly journals Fuzzy Programming Approaches for Modeling a Customer-Centred Freight Routing Problem in the Road-Rail Intermodal Hub-and-Spoke Network with Fuzzy Soft Time Windows and Multiple Sources of Time Uncertainty

Mathematics ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 739 ◽  
Author(s):  
Sun ◽  
Li
Keyword(s):  
Time Windows ◽  
Fuzzy Programming ◽  
Service Level ◽  
Mixed Integer ◽  
Chance Constrained Programming ◽  
Multiple Sources ◽  
Routing Problem ◽  
Hub And Spoke ◽  
Soft Time Windows ◽  
Time Uncertainty

In this study, we systematically investigate a road-rail intermodal routing problem the optimization of which is oriented on the customer demands on transportation economy, timeliness and reliability. The road-rail intermodal transportation system is modelled as a hub-and-spoke network that contains time-flexible container truck services and scheduled container train services. The transportation timeliness is optimized by using fuzzy soft time windows associated with the service level of the transportation. Reliability is enhanced by considering multiple sources of time uncertainty, including road travel time and loading/unloading time. Such uncertainty is modelled by using fuzzy set theory. Triangular fuzzy numbers are adopted to represent the uncertain time. Under the above consideration, we first establish a fuzzy mixed integer nonlinear programming model with a weighted objective that includes minimizing the costs and maximizing the service level for accomplishing transportation orders. Then we use the fuzzy expected value model and fuzzy chance-constrained programming separately to realize the defuzzification of the fuzzy objective and use fuzzy chance-constrained programming to deal with the fuzzy constraint. After defuzzification and linearization, an equivalent mixed integer linear programming (MILP) model is generated to enable the problem to be solved by mathematical programming software. Finally, a numerical case modified from our previous study is presented to demonstrate the feasibility of the proposed fuzzy programming approaches. Sensitivity analysis and fuzzy simulation are comprehensively utilized to discuss the effects of the fuzzy soft time windows and time uncertainty on the routing optimization and help decision makers to better design a crisp transportation plan that can effectively make tradeoffs among economy, timeliness and reliability.

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