Concurrent optimization of mountain railway alignment and station locations using a distance transform algorithm

Pu, Hao; Zhang, Hong; Li, Wei; Xiong, Jiaxing; Hu, Jianping; Wang, Jie

doi:10.1016/j.cie.2018.01.004

Cited by 43 publications

(26 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Li et al [29,30] used a genetic algorithm and bidirectional distance transform to optimize railway alignments in mountainous terrain. Concurrent optimization of mountain railway alignment and station locations using a distance transform algorithm was recently reported by Pu et al [31].…”

Section: Literature Reviewmentioning

confidence: 99%

A Model for Optimizing Railway Alignment Considering Bridge Costs, Tunnel Costs, and Transition Curves

2019

View full text Add to dashboard Cite

Owing to wide-ranging searches (there are various alignments between two points) as well as complex and nonlinear cost functions and a variety of geometric constraints, the problem of optimal railway alignment is classified as a complex problem. Thus, choosing an alignment between two points is usually done based on a limited number of alignments designed by experts. In recent years, the study of railway alignment optimization has shown the importance of optimization and the introduction of various algorithms and their usefulness in solving different problems. It is expected that applying meta-heuristic optimization algorithms such as methods based on swarm intelligence can lead to better alignments. In this study, we tried to modify models based on previous studies in order to design and develop a model based on a single framework to provide three-dimensional optimization of alignments applicable in the real world. To obtain this, the particle swarm algorithm is used and a geographic information system is incorporated as a means of search in three-dimensional space. In particular, the cost function used in previous studies considering the costs related to structures (bridges and tunnels) are improved regarding hydraulic structure alignments. Furthermore, the transition curve of horizontal alignment and slope restrictions of curves are considered in this project by using the penalty function in order to obtain the most practical results possible. Finally, this study examines three problems for which the results are acceptable in cases of railway alignment geometry and its application in the real world.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

A Model for Optimizing Railway Alignment Considering Bridge Costs, Tunnel Costs, and Transition Curves

2019

View full text Add to dashboard Cite

show abstract

“…Furthermore, based on the bidirectional DT, Pu et al. () optimized railway alignment and terminal locations concurrently by handling more constraints compared with separately optimizing railway alignment or terminal locations.…”

Section: Introductionmentioning

confidence: 99%

“…The usual goal of alignment optimization is to find an alignment with the lowest comprehensive cost between two given endpoints. In the literature, representative methods for optimizing alignments include particle swarm optimization (Shafahi & Bagherian, 2013;Babapour, Naghdi, Ghajar, & Mortazavi, 2018;Pu et al, 2019), two-stage method that combines global optimization methods with a gradient type algorithm (Vázquez-Méndez, Casal, Santamarina, & Castro, 2018), derivative-free algorithms (Mondal, Lucet, & Hare, 2015), discrete algorithms (Hirpa, Hare, Lucet, Pushak, & Tesfamariam, 2016;, dynamic programming (Hogan, 1973;Li, Pu, Zhao, & Liu, 2013), mixed integer programming (Easa & Mehmood, 2008), linear programming (Revelle, Whitlatch, & Wright, 1996;Chapra & Canale, 2006), network optimization (Trietsch, 1987a(Trietsch, , 1987b), heuristic neighborhood search with mixed integer programming (Cheng & Lee, 2006;Lee, Tsou, & Liu, 2009), calculus of variations (Howard, Bramnick, & Shaw, 1968), numerical search (Robinson, 1973), enumeration (Easa, 1988), average-end-area method for improving earthwork calculation accuracy from 2D to 3D (Cheng & Jiang, 2013), genetic algorithms (Maji & Jha, 2009, and distance transforms (DTs) (de Smith, 2006;Li et al, 2016;Li et al, 2017;Pu et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…Such improvements can overcome the difficulties of determining the appropriate distribution of cutting planes in mountainous regions for the GA and optimizing paths for the DT. Furthermore, based on the bidirectional DT, Pu et al (2018) optimized railway alignment and terminal locations concurrently by handling more constraints compared with separately optimizing railway alignment or terminal locations.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A three‐dimensional distance transform for optimizing constrained mountain railway alignments

Song

Schonfeld

et al. 2019

Computer aided Civil Eng

Self Cite

View full text Add to dashboard Cite

Railway alignment optimization is considered one of the most complicated and time‐consuming problems in railway planning and design. It requires searching among the infinite potential alternatives in huge three‐dimensional (3D) search spaces for a near‐optimal alignment, while considering complex constraints and a nonlinear objective function. In mountainous regions, the complex terrain and constructions require additional and more complex constraints than in topographically simpler regions. In this paper, the authors solve this problem with an algorithm based on a 3D distance transform (3D‐DT). Compared with previous two‐dimensional distance transform (2D‐DT) methods developed in this field, the feasible search spaces of 3D‐DT are greatly increased. Consequently, this new method can find more alternatives with higher qualities. In this approach, an erythrocyte‐shaped 3D neighboring mask is developed to narrow local search spaces and speed up the search process. Besides, a stepwise‐backstepping strategy is designed to dynamically determine feasible 3D search spaces and efficiently search the study area. During the 3D‐DT search process, multiple constraints, including geometric, construction, and location constraints, are effectively handled. After the 3D‐DT search, a genetic algorithm is employed to optimize the 3D‐DT paths into final alignments. Finally, this novel approach is applied to an actual case in a complex mountainous region. The comprehensive cost of the best solution generated by 3D‐DT is 16% below a manual solution produced by very experienced human designers. Furthermore, the total number of feasible alternatives found by 3D‐DT is 4.3 times greater than by 2D‐DT. The comprehensive cost of the best 3D‐DT solution is 10% below the best one generated by 2D‐DT.

show abstract

“…Jha [2] expanded upon the Jong and Schonfeld [1] highway alignment optimization model by considering the spatial analysis environment, in order to develop a geographic information system-based highway optimization model. Several studies specifically explored railway alignment optimization in mountainous terrain [3][4][5]. Lai and Schonfeld [6] jointly optimized the alignment of rail transit and its station locations, given that the location of a station can effect demand distributions and spacing between stations can affect travel times.…”

Section: Introductionmentioning

confidence: 99%

Post-Construction Alignment Revision in Direct-Fixation Railroad Tracks

Kim

Delos

et al. 2019

Sustainability

View full text Add to dashboard Cite

In railroad construction—in particular, direct-fixation tracks—a longitudinal concrete block known as a “plinth” is used to elevate the profiles of the railroad track from the aerial guideway (e.g., bridge deck). A post-construction alignment revision is often required if the plinth elevation surpasses its maximum tolerance after the concrete pour. In such cases, the plinth surface needs to be grinded to meet the design elevation, or a shim should be inserted underneath the rail pad to raise the profile elevation. Considering both sides of the rail plinths, vertical design factors, and performance specifications, re-optimization of the vertical profile is of great interest, but the process poses challenges and represents a practical research problem. An optimization model aimed at minimizing the cost of post-construction alignment repairs is proposed and a real-case numerical example is analyzed to check the effectiveness of the model.

show abstract

Concurrent optimization of mountain railway alignment and station locations using a distance transform algorithm

Cited by 43 publications

References 27 publications

A Model for Optimizing Railway Alignment Considering Bridge Costs, Tunnel Costs, and Transition Curves

A Model for Optimizing Railway Alignment Considering Bridge Costs, Tunnel Costs, and Transition Curves

A three‐dimensional distance transform for optimizing constrained mountain railway alignments

Post-Construction Alignment Revision in Direct-Fixation Railroad Tracks

Contact Info

Product

Resources

About