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Multi-objective railway alignment optimization considering costs and environmental impacts

Hong Zhang,Hao Pu,P. Schonfeld,Taoran Song,Jie Wang,Xianbao Peng,Jianping Hu

Published 2020 in Applied Soft Computing

ABSTRACT

Abstract With increasing transportation requirements in mountainous regions, railways are encroaching ever more on environmentally-sensitive areas in those regions. Selecting an economical and eco-friendly railway alignment can effectively minimize negative impacts on mountain environments while also reducing costs. To this end, this paper formulates the alignment design problem as a multi-objective optimization model, which includes both economic and environmental objectives. Two new quantitative indexes for measuring environmental impacts are proposed to reflect the degree of vegetation destruction and soil erosion. A multi-objective optimization method based on the particle swarm optimization (PSO) algorithm is proposed for seeking non-dominated solutions. New update mechanisms for dealing with the multi-objective optimization problem are devised. A local repair algorithm based on a customized crossover operator is designed to save promising alignment alternatives during the search process. Two real-world cases are used to demonstrate the effectiveness of the proposed method. The results show that it can trade off the economic and environmental objectives and bypass all the pre-specified forbidden zones, thus providing designers a set of non-dominated alignment alternatives.

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