2012 ◽  
Vol 204-208 ◽  
pp. 1648-1651
Author(s):  
Xiao Yu Sun ◽  
Zhen Qing Wang ◽  
Hong Tao Xing ◽  
Yong Heng Tong

In this paper we propose a stepwise genetic algorithms approach for optimizing highway alignments for improving computational efficiency and quality of solutions. Our previous work in highway alignment optimization has demonstrated that computational burden is a significant issue when working with a geographic information system (GIS) database requiring numerous spatial analyses. For solving real-world problems working directly with real maps through a GIS is highly desirable. Furthermore, saving computation time can enhance adoptability of a model especially when a study area is relatively large, or involves many sensitive properties, or if locating complex structures such as intersections, bridges and tunnels is necessary. It is well acknowledged that in many optimization processes subdividing large problems into smaller pieces can decrease the computation time and produce a better solution. In this research two different population sizes are used to develop a stepwise alignment optimization when employing genetic algorithms in suitably subdivided study areas. An example study shows that the proposed stepwise optimization gives more efficient results than the existing methods and also improves quality of solutions.


Author(s):  
Avijit Maji ◽  
Manoj K. Jha

Usually, selection of a highway alignment depends on an economical route that minimizes alignment sensitive costs, such as construction cost, user cost, right-of-way cost, and earthwork cost. Most of the available highway alignment optimization algorithms do not consider traffic assignment and distribution of traffic as a result of the new road network consisting of the new alignment as well as other pre-existing alignments. Constructing a new highway will ease the traffic in the existing road network. Based on Wardrop’s principle, the users will choose a route that will minimize their travel-time. Users will unilaterally shift to the available routes for their benefit and thus, traffic flow will attain equilibrium. Theoretically, the equilibrium of traffic flow between the existing highway and the newly designed highway alternative can be achieved by a user equilibrium model. A new methodology is developed in this paper to optimize a new three-dimensional highway alignment based on the existing highway alignment system information using a cost-benefit analysis approach. The results are quite promising for new road design and bypass construction since benefit maximization and cost minimization is performed simultaneously while attaining user equilibrium.


2011 ◽  
Vol 58-60 ◽  
pp. 1499-1503 ◽  
Author(s):  
Jian Xin Chen ◽  
Yong Yi Guo ◽  
Mai Xia Lv

Based on the characteristics of the highway design, this paper transfers all the factors involved in the highway design to a cost-optimized-oriented model and designs a variety parallel genetic algorithm to optimize highway design. While maintaining evolution stability of excellent individual, the algorithm can improve convergence rate and accuracy and avoid premature convergence generated by single-population evolution. To some extent, it makes up generalization-lacking defects of a single species or steady parameters in premature overcoming. Finally, the algorithm is verified with a good result. This algorithm provides a useful method for highway design.


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