scholarly journals Half Open Multi-Depot Heterogeneous Vehicle Routing Problem for Hazardous Materials Transportation

2021 ◽  
Vol 13 (3) ◽  
pp. 1262
Author(s):  
Zhongxin Zhou ◽  
Minghu Ha ◽  
Hao Hu ◽  
Hongguang Ma

How to reduce the accidents of hazardous materials has become an important and urgent research topic in the safety management of hazardous materials. In this study, we focus on the half open multi-depot heterogeneous vehicle routing problem for hazardous materials transportation. The goal is to determine the vehicle allocation and the optimal route with minimum risk and cost for hazardous materials transportation. A novel transportation risk model is presented considering the variation of vehicle loading, vehicle types, and hazardous materials category. In order to balance the transportation risk and the transportation cost, we propose a bi-objective mixed integer programming model. A hybrid intelligent algorithm is developed based on the ε-constraint method and genetic algorithm to obtain the Pareto optimal solutions. Numerical experiments are provided to demonstrate the effectiveness of the proposed model. Compared with the close multi-depot heterogeneous vehicle routing problem, the average risk and cost obtained by the proposed bi-objective mixed integer programming model can be reduced by 3.99% and 2.01%, respectively. In addition, compared with the half open multi-depot homogeneous vehicle routing problem, the cost is significantly reduced with the acceptable risk.

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Bochen Wang ◽  
Qiyuan Qian ◽  
Zheyi Tan ◽  
Peng Zhang ◽  
Aizhi Wu ◽  
...  

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.


2021 ◽  
Vol 13 (6) ◽  
pp. 3188
Author(s):  
Byungjun Ju ◽  
Minsu Kim ◽  
Ilkyeong Moon

Troop movement involves transporting military personnel from one location to another using available means. To minimize damage from enemies, the military simultaneously uses reconnaissance and transportation units during troop movements. This paper proposes a vehicle routing problem considering reconnaissance and transportation (VRPCRT) for wartime troop movements. The VRPCRT is formulated as a mixed-integer programming model for minimizing the completion time of wartime troop movements and reconnaissance, and transportation vehicle routes were determined simultaneously in the VRPCRT. For this paper, an ant colony optimization (ACO) algorithm for the VRPCRT was also developed, and computational experiments were conducted to compare the ACO algorithm’s performance and that of the mixed-integer programming model. The performance of the ACO algorithm was shown to yield excellent results even for the real-size problem. Furthermore, a sensitivity analysis of the change in the number of reconnaissance and transportation vehicles was performed, and the effects of each type of vehicle on troop movement were analyzed.


2014 ◽  
Vol 931-932 ◽  
pp. 578-582
Author(s):  
Sunarin Chanta ◽  
Ornurai Sangsawang

In this paper, we proposed an optimization model that addresses the evacuation routing problem for flood disaster when evacuees trying to move from affected areas to safe places using public transportation. A focus is on the situation of evacuating during high water level when special high vehicles are needed. The objective is to minimize the total traveled distance through evacuation periods where a limited number of vehicles is given. We formulated the problem as a mixed integer programming model based on the capacitated vehicle routing problem with multiple evcuation periods where demand changing by the time. The proposed model has been tested on a real-world case study affected by the severe flooding in Thailand, 2011.


2019 ◽  
Vol 206 ◽  
pp. 976-986 ◽  
Author(s):  
Gustavo A. Bula ◽  
H. Murat Afsar ◽  
Fabio A. González ◽  
Caroline Prodhon ◽  
Nubia Velasco

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