Optimum Point of Intersection Selection in Horizontal Highway Alignment Design: A Comparative Study Using Path Planner Method and Ant Algorithm

Sushma, M.B.; Roy, Sandeepan; Prasad, Mritunjay; Maji, Avijit

doi:10.1007/978-981-32-9042-6_15

Cited by 3 publications

(1 citation statement)

References 16 publications

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“…For the continuous optimization problem, a model can be formulated as P = (S Ω•f), where S defines all finite sets of discrete decision variables, Ω defines constraints between variables and a target function (f : S → R0+) which must be minimized or maximized [43], [45]. It should be noted that in ant colony optimization, the basis of work is the gradual construction of solutions based on the probability of solution components and the probability values are calculated based on the pheromone values of each component [46], [47]. In ant colony optimization implemented in hybrid optimization problems, a set of parts related to the solution available is defined by the problem formula [48].…”

Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel

Afradi¹,

Ebrahimabadi²,

Hallajian³

2020

Min. miner. depos.

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The purpose of this study is to use a novel approach to estimate the tunnel boring machine (TBM) penetration rate in diverse ground conditions. Methods. The methods used in this study include ant colony optimization (ACO), bee colony optimization (BCO) and the particle swarm optimization (PSO). Moreover, a comprehensive database was created based on machine performance using penetration rate (m/h) as an output parameteras well as intact rock and rock mass parameters including uniaxial compressive strength (UCS) (MPa), Brazilian tensile strength (BTS) (MPa), rock quality designation (RQD) (%), cohesion (MPa), elasticity modulus (GPa), Poisson's ratio, density(g/cm 3 ), joint angle (deg.) and joint spacing (m) as input parameters. Findings. Results showed that the analyses yielded several realistic and reliable models for predicting penetration rate of TBMs. ACO model has R 2 = 0.8830 and RMSE = 0.6955, BCO model has R 2 = 0.9367 and RMSE = 0.5113 and PSO model has R 2 = 0.9717 and RMSE = 0.3418. Originality. Prediction of TBM penetration rate using these methods has been carried out in the Sabzkooh water conveyance tunnel for the first time. Practical implications. According to the results, all three approaches are very effective but PSO yields more precise and realistic findings than other methods.

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Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel

Afradi¹,

Ebrahimabadi²,

Hallajian³

2020

Min. miner. depos.

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Auxiliary Road Design and Optimization for Railway Construction in Mountainous Areas

Wang,

Gao,

Gan

et al. 2023

J. Transp. Eng., Part A: Systems

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GIS Spatial Optimization for Corridor Alignment Using Simulated Annealing

et al. 2020

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Planning corridors for new facilities such as pipeline or transmission lines through geographical spaces is a topographical constraint optimization problem. The corridor planning problem requires finding an optimal route or a set of alternative paths between two locations. This article presents a simulated-annealing-based (SA) approach applying a variable neighborhood strategy in a continuous space to generate competitive and different alternative paths to solve the corridor planning problem. The variable neighborhood method randomly selects two points from a variable interval of the current solution generated by SA creating pseudo-random paths inside a corridor and finding spatially different alternatives. The proposed approach is evaluated with three practical problems using real topographic data from the Veracruz Basin in Mexico. The experimental results show that this approach obtains efficient and competitive solutions with improvements above 18% over those gotten by the compared method.

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Optimum Point of Intersection Selection in Horizontal Highway Alignment Design: A Comparative Study Using Path Planner Method and Ant Algorithm

Cited by 3 publications

References 16 publications

Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel

Prediction of tunnel boring machine penetration rate using ant colony optimization, bee colony optimization and the particle swarm optimization, case study: Sabzkooh water conveyance tunnel

Auxiliary Road Design and Optimization for Railway Construction in Mountainous Areas

GIS Spatial Optimization for Corridor Alignment Using Simulated Annealing

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