Abstract
As an indispensable necessity in daily routine of citizens, hazardous materials (Hazmat) not only plays an increasingly important role, but also brings a series of transportation uncertainty phenomena, the most prominent of which is a safety problem. When it attempts to find the best vehicle route scheme that can possess the lowest risk attribute in a fuzzy random environment for a single warehouse, the influence of cost should also be taken into account. In this study, a new mathematical theory was conducted in the modeling process. To take a full consideration of uncertainty, vehicle travel distance and population density along the road segment were assumed to be fuzzy variables. Meanwhile, accident probability and vehicle speed were set to be stochastic. Furthermore, based on the assumptions, authors established three chance constrained programming models according to the uncertain theory. Model I was used to seek the achievement of minimum risk of the vehicle route scheme, using traditional risk model; the goal of Model II was to obtain the lowest total cost, including the green cost, and the main purpose of Model III was to establish a balance between cost and risk. To settle the above models, a hybrid intelligent algorithm was designed, which was a combination of genetic algorithm and fuzzy random simulation algorithm, which simultaneously proved its convergence. At last, two experiments were designed to illustrate the feasibility of the proposed models and algorithms.
Highlights
With the evolution of industrial society, the demand for the logistics industry, especially hazardous materials, which are different from ordinary goods in physical nature and are considered as moving “hazard source” in the transportation process, is constantly increasing
As risk and cost happening during hazmat transportation have dual attribute, a VRP model using chance measure was considered in this study; a detailed introduction on fuzzy random theory is first presented
For example, explanation and value for parameters used in Equation (9) are listed as follows: Authors assume that the vehicle travels through a given arc (i,j) at the speed vi j, the total quantity Fij of energy consumed on arc can be approximated as: Fij = Pt × = (Mi j avi j + Mi j gvi j sinθ + 0.5Cd Sζvi j 3 + Mi j gvi j Ch cosθ) ×
Summary
With the evolution of industrial society, the demand for the logistics industry, especially hazardous materials, which are different from ordinary goods in physical nature and are considered as moving “hazard source” in the transportation process, is constantly increasing. Public consciousness responding to danger is gradually strengthened, which forced the world to cope with the challenge that hazmat brings In this condition, any minor uncertainty factor is likely to give rise to risk increment during transportation, bringing decision-making changes of vehicle routing arrangement. In view of the above requirements, this study will study fuzzy and random factors that occurred in the hazmat transportation, consider multiple demands of supply chain participants, such as the minimum risk value, which is the ideal state the government hopes to achieve, and the minimum cost, which is the goal enterprise pursued.
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