Abstract
In the process of transportation system construction, the tunnel is always an indispensable part of the traffic network due to terrain constraints. A collapse of the tunnel under construction may give rise to a potential for significant damage to the traffic network, complicating the road conditions and straining relief services for construction workers. To cope with the variety of vehicle types during the rescue effort, this paper divides them into small, medium, and large sizes, herein correcting the corresponding speed considering six road condition factors on account of the previous research. Given the influence of different special road conditions on the speed of different sized vehicles, a multi-objective model which contains two stages is presented to make decisions for rescue vehicle scheduling. Under the priority of saving human life, the first-stage objective is minimizing the arrival time, while the objective of the second stage includes minimizing the arrival time, unmet demand level, and scheduling cost. To solve the currently proposed model, a non-dominated sorting genetic algorithm II (NSGA-II) with a real number coding method is developed. With a real tunnel example, the acceptability and improvement of the model are examined, and the algorithm’s optimization performance is verified. Moreover, the efficiency of applying real number coding to NSGA-II, the multi-objective gray wolf algorithm (MOGWO), and the traditional genetic algorithm (GA) is compared. The result shows that compared with the other two methods, the NSGA-II algorithm converges faster.
Highlights
We first explain the improvement of the non-dominated sorting genetic algorithm II (NSGA-II) algorithm applied in this paper and compare the efficiency of the NSGA-II algorithm used in this study, the multi-objective gray wolf algorithm, and the general genetic algorithm based on the real number coding method
This paper proposed a theory to optimize the scheduling plan of the rescue vehicles after a tunnel collapse in view of the different vehicles’ sizes and the priority of the objectives in different stages
The rescue vehicles were divided into three sizes, including small, medium, and large, and the speed corrections on the road with special conditions were performed for each size of the vehicle
Summary
For mountainous countries such as China, the tunnel is an essential component of the transportation network. The emergency rescue vehicles (includes special vehicles such as ambulances, engineering rescue vehicles, cranes, etc.) differentiate according to the characteristics of ultra-high, ultra-wide, and heavy-duty, requiring special road conditions for passing. This highlights the need for suitable vehicle scheduling routes with characteristics that could minimize the limitation of passage for different sizes of vehicles, ensuring the arrival time of rescue efforts, saving the lives of trapped constructors, and reducing property losses. We propose a two-stage model to determine the scheduling plan of rescue vehicles according to their size to reduce the impact of road conditions. A comparison of the NSGA-II algorithm, the multi-objective gray wolf algorithm (MOGWO), and the general genetic algorithm (GA) are provided
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