Vehicle routing optimum model of hazardous materials transportation under fuzzy environment

Abstract

Due to the larger and larger proportion of hazardous material (hazmat) transportation occupying in the national economy, more and more researchers focus on this field. With the mature of fuzzy theory, this paper puts forward a model with three constraints, they are capacity, time window, risk respectively. It assumes that the travel time and the risk are both fuzzy variables, the risk is calculated by the affected people number multiply the accident probability. The goal is to obtain the best route schedule under the three constraints. This paper simultaneously designs the genetic algorithm based on fuzzy simulation. In the end, two cases are given to illustrate the efficiency of the proposed model and algorithm.

Keywords

Hazardous material (hazmat) transportation fuzzy theory three constraints best route schedule

Get full access to this article

View all access options for this article.

References

Liu

and Iwamura

, Chance constrained programming with fuzzy parameters, Fuzzy Sets and Systems94(2) (1998), 227–237.

Liu

, Uncertain Theory: An Introduction to its Axiomatic Foundations, Springer, Berlin, (2004).

C.X.

, Li

Y.Z.

and He

R.C.

, Route optimisation models and algorithms for hazardous materials transportation under different environments, Int J Bio-Inspired Comput5(4) (2013), 252–265.

Erkut

and Verter

, Modeling of transport risk for hazardous materials, Operations Research46(5) (1998), 625–642.

Erkut

and Ingolfsson

, Transport risk models for hazardous materials: Revisited, Operations Research Letters33(1) (2005), 81–89.

Erkut

, Tjandra

S.A.

and Verter

, Hazardous materials transportation, Handbooks in Operations Research and Management Science14(2007), 539–539.

Zhao

and Verter

, A bi-objective model for the used oil location-routing problem, Computers & Operations Research62(2015), 157–168.

Zografos

K.G.

and Androutsopoulos

K.N.

, A decision support system for integrated hazardous materials routing and emergency response decisions, Transportation Research Part C: Emerging Technologies16(6) (2008), 684–703.

Toumazis

and Kwon

, Routing hazardous materials on time-dependent networks using conditional value-at-risk, Transportation Research Part C: Emerging Technologies37 (2013), 73–92.

10.

Wei

M.Y.

, Yu

and Li

, Credibilistic Location-Routing Model for Hazardous Materials Transportation, International Journal of Intelligent Systems30(1) (2015), 23–39.

11.

Wei

M.Y.

, Li

and Yu

, Time-dependent fuzzy random location-scheduling programming for hazardous materials transportation, Transportation Research Part C: Emerging Technologies57(2015), 146–165.

12.

National Bureau of Statistics of the People’s Republic of China, http://www.stats.gov.cn/tjsj/ndsj/

13.

Berglund

P.G.

and Kwon

, Robust facility location problem for hazardous waste transportation, Networks and Spatial Economics14(1) (2014), 91–116.

14.

Zheng

and Liu

, Fuzzy vehicle routing model with credibility measure and its hybrid intelligent algorithm, Applied Mathematics and Computation176(2) (2006), 673–683.

15.

Zhou

, Chu

and Che

, A multi-objective model for the hazardous materials transportation problem based on lane reservation, Networking, Sensing and Control (ICNSC), 9th IEEE International Conference on Networking, Sensing and Control, (2012). Beijing, China.