Optimum Curvature Principle In Highway Routing

Howard, Bernard E.; Bramnick, Zacarias; Shaw, Jocelyn F. B.

doi:10.1061/jhcea2.0000266

Cited by 52 publications

(5 citation statements)

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“…Therefore, most of the studies are dedicated to the search for routes. The early research methods include the optimum curvature principle (Howard et al., 1968), linear programming (Lee et al., 2009), dynamic programming (DP) (Goh et al., 1988), and mixed‐integer linear programming (Hare et al., 2015). In recent years, several new approaches have been tried in the field of route optimization.…”

Section: Literature Reviewmentioning

confidence: 99%

Biobjective optimization for railway alignment fine‐grained designs with parallel existing railways

Gao,

Zhang,

Zhu

et al. 2024

Computer aided Civil Eng

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Urban high‐speed railway construction is complex due to limited land resources, high population density, and potential construction risks, especially when new tracks are parallelly aligned to operational railways. Addressing a gap in current literature on fine optimization of manual alignment in such scenarios, this paper introduces a biobjective approximate fine‐grained optimization model for railway alignments (BA‐FORA). Utilizing an approximate dynamic programming (ADP) method, BA‐FORA effectively searches the feasible region to approach a global optimum, overcoming the dimensionality challenges inherent in standard dynamic programming (DP). This paper presents a biobjective optimization framework that takes into account both construction cost and construction risk adjacent to existing operating railways (CRAEOR), offering a method for the fine‐grained design of new railways adjacent to existing railways. Finally, the proposed BA‐FORA framework is applied to practical cases, demonstrating its superior optimization performance. The findings indicate that the BA‐FORA model can autonomously investigate and enhance railway alignment. It generates cost‐effective and low‐risk solutions exceeding manual efforts, ensuring alignment constraint compliance.

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Section: Literature Reviewmentioning

confidence: 99%

Biobjective optimization for railway alignment fine‐grained designs with parallel existing railways

Gao,

Zhang,

Zhu

et al. 2024

Computer aided Civil Eng

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show abstract

“…In order to integrate, the cost function should be continuous between the two points of interest, which is very unlikely in real world problems. Based on this principle, Howard et al (1968) developed the Optimum Curvature Principle (OCP) for horizontal highway alignment design model. This model was applied in finding a maritime route through dynamic ice field (Thomson & Sykes, 1988) and horizontal alignment of an expressway in flat south Florida (Shaw & Howard, 1982).…”

Section: Highway Alignment Optimizationmentioning

confidence: 99%

Highway Alignment Optimization Using Cost-Benefit Analysis Under User Equilibrium

Maji¹,

Jha

2011

International Journal of Operations Research and Information Systems

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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.

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“…Early studies on alignment optimization proposed some mathematical algorithms for solving such problems, such as calculus of variations (Howard et al., 1968), numerical search (Robinson, 1973), and enumeration (Easa, 1988). Then, with the rapid development of computer technology, more methods were developed for solving three types of alignment optimization problems.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous optimization of 3D alignments and station locations for dedicated high‐speed railways

Schonfeld

Zhang

et al. 2021

Computer aided Civil Eng

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Determinations of alignments and station locations are major tasks in railway design, which jointly and fundamentally influence the construction and operation of the whole project. Currently, although considerable efforts have been invested into the separate optimization of alignments or station locations, the complex interactions between alignments and stations, as well as their concurrent impacts on railways still need further investigations. Therefore, this study focuses on modeling and optimization of passenger railway alignments and station locations simultaneously. A novel optimization model is formulated for maximizing net present value (NPV) considering comprehensive costs and revenue from riders over the railway's design life. Specifically, the comprehensive cost includes construction and operation costs of alignments and stations. The railway ridership is quantified by combining travel time and trip coverage using a logit function. Then, the railway revenue is estimated and combined with costs through an economic growth model to obtain the NPV. To solve this model, two customized and mutually exclusive methods, that is, the station‐alignment‐integration (SAI) and alignment‐station‐integration (ASI) methods, are developed based on a particle swarm algorithm. The SAI primarily searches for possible stations in the landscape and then generates alignments to connect adjacent stations. The ASI directly yields the main alignment, on which potential stations are located by handling specific constraints. The model and methods are applied to an actual high‐speed railway. Results show that both SAI‐ and ASI‐generated railways have higher NPV values compared to the corresponding railway designed by experienced designers. Sensitivity analysis reveals that SAI is more flexible than ASI in solving actual cases. The convergence of the proposed methods is also discussed. With some changes in input parameters based on locally applicable design standards, the proposed methods are generally applicable to other cases or countries.

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Optimum Curvature Principle In Highway Routing

Cited by 52 publications

References 0 publications

Biobjective optimization for railway alignment fine‐grained designs with parallel existing railways

Biobjective optimization for railway alignment fine‐grained designs with parallel existing railways

Highway Alignment Optimization Using Cost-Benefit Analysis Under User Equilibrium

Simultaneous optimization of 3D alignments and station locations for dedicated high‐speed railways

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