Swarm Intelligence Algorithms For The 3D Route Location In Highway (Railway) Engineering Structures

Linear engineering structures such as highway or railway in China are in booming development, and the country has been pouring money into these projects each year. Route location, which is a kind of overall work in road alignment survey and design, is the preliminary work of a project. It is very important when dealing with a linear engineering. The location of the route has great influence on construction costs, operating expenses, and environmental impacts on the study area. A traditional method solves the complicated problem by repeated comparison of the corridor, location and geometric parameter for the linear engineering structures, while a modern one demands not only a good alignment in all affairs but also the efficiency to design the structure. Requirements for the further improving the method are put forward for the route location.The swarm intelligence optimization algorithm is a kind of modern optimization method, and more and more attention has been paid to the research field. Some animals have exhibited complex social behaviors. A most surprising behavioral patterns exhibited by ants is the ability of certain ant species to find what computer scientists call shortest paths, and another one is a population-based optimization technique inspired by the motion of a bird flock, or fish schooling. It is this behavioral pattern that inspired computer scientists to develop algorithms for the solution of optimization problems. The optimization methodology of the swarm intelligence algorithm is the interaction of information and the cooperation between the individuals. The methods are simple and efficient compared to other traditional methods. Although the research for the intelligence optimization has attains plenty of important achievements, the new research field is still open and further research works on how to raise the calculation efficiency, and how to integrate the method with the realistic problem should be given.This dissertation focuses the attention on finding a realistic three-dimensional route alignment. Around this issue, ant colony optimization (ACO) and particle swarm optimization (PSO) algorithm and their applications in the route location automatically are researched.This dissertation focuses on the following works:(1) Ant colony optimization algorithm for the vertical alignment of route. (2) Improving performance about swarm intelligence optimization algorithm. (3) Method of route location in 3D space (4) Earthwork allocation model for nonlinear factors.The main works and contributions of this dissertation are as follows:Researches on the vertical profile:an optimization method to produce an optimum vertical highway or railway profile for a pre-selected horizontal alignment is developed based on discrete theory. The aim of the program was to establish an initial vertical alignment according to discreet ground elevation of station. Considering the discreet characteristic of the ground elevation and the intersection point of grade line, a discrete model is presented. The automatic design problem is set to select the number, location and elevation of the intersection point of the grade line after considering several designing constraints.The two swarm intelligence optimization algorithms (ACO and PSO) are impoved:(1)A combination approach with local pheromone update ruler, elitist ants and MAX-MIN ant system (MMAS) is designed for not only developing the ant search scope, but also strengthening the ability of the ants to pass the complex space. The method combines probabilistic selection and deterministic selection to design transition probability. Some key factors for pheromone update, selection mechanism and allowed set strategy also are researched.(2) A two-stage probing method (RPSO) is proposed to improve PSO method. The first stage guarantees the particle to get away from feasible region as little probability as possible, and the second stage probes further to overcome local minima by Rosenbrock method. The proposed method is implemented and tested for several functions. The results show that the combining method demonstrates a quite good performance in finding global minima reliably in dealing with multidimensional variables and multiple constraints.As for as route location in 3D space, the problem is broken into two parts:one is a corridor finding, another is 3D alignment location. The former aims at a coarse route location while the latter aims at a local alignment and parameter calculation.The first stage of the research on route location in 3D space:(1) A space model consisted in axes and layers are proposed in accordance with route location space, which is an improvement on the traditional plane grids model to seek a corridor.(2) A corridor alignment construction approach on 3D axis and layer model, which is based on an ACO algorithm, is proposed. It can search a good solution on a large discrete space by allowed sets strategy, and a digital example proves its feasibility on the 3D grids elevation model.(3) Right-of-way costs including those associated with land and environmental impacts as well as impacts to stream and other water conduits. A strategy on combining the 3D right-of-way cost model with the 3D grids elevation model is proposed for the cost calculation in the grid point search process.The second stage of the research on route location in 3D space:(1) A PSO model for simultaneously optimizing three-dimensional highway or railway alignments is proposed to get the alignments parameter and location.(2) The experiment about route location has proved that RPSO algorithm has high computational efficiency in calculating earthwork quantity on digital elevation models (DEM) with multidimensional variables and multiple constraints.In the end, a new optimized highway earthwork allocation model from mass-haul diagram idea is built for nonlinear nature. The model aims at generating the optimal earthmoving plan automatically. With it, the earth moving operations can be represented as discrete events systems, and an ant colony optimization algorithm is developed to be equipped with the model.