Quantum-inspired immune clonal algorithm for railway empty cars optimization based on revenue management and time efficiency

Jing, Yun; Liu, Yingke; Bi, Mingkai

doi:10.1007/s10586-017-1292-7

Cited by 4 publications

(2 citation statements)

References 6 publications

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“…Because design is an important factor to determine the project cost. Taking the technical route of comprehensive cost management and taking the four aspects of the whole process, the whole risk, the whole team and the whole factor cost management as the starting point, this paper puts forward relevant suggestions and measures for cost management in the design stage, in order to achieve better control effect of project cost [13]. Based on the research and analysis of the whole process, whole life cycle and total cost management, Nanchian et al put forward the cost management theory and method suitable for China's government investment projects, and established the evaluation design for the investment scheme [14].…”

Section: Related Workmentioning

confidence: 99%

Dynamic Cost Estimation of Reconstruction Project Based on Particle Swarm Optimization Algorithm

Li¹

2023

IJCAI

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This paper proposes the research on dynamic cost estimation of reconstruction project in accordance with the particle swarm optimization procedure in order to predict the value of dynamic cost estimation of reconstruction project. To accomplish the task initially the applicability of example swarm optimization procedure is introduced. The basic principle of particle swarm optimization procedure is described, and PSO (particle swarm optimization) procedure is used to optimize the super factors of LS-SVM. The spss20.0 statistics is used to cluster the sample data to obtain similar engineering classes. BP-NN (Back Propagation Neural Network), LS -SVM, and PSO-LSSVM are implemented to anticipate and simulate the development price for the authentication of request effect of the optimized design in that area. The results show that the relative errors of the three designs are controlled within + 10%, this may be used in the early stages of building to anticipate construction costs accurately. The range of the relative error dissemination interval predicted using the BP-NN design is 13.12% and is between [-7.46%, 5.74%]. The range of the relative error dissemination interval predicted by the LS SVM design is 14.22% and is between [-8.12%, 6.17%]. According to the PSO-LSSVM design, the relative error dissemination interval is [-2.56%, 2.49%], and its range is 5.21%. In terms of prediction stability and robustness, the prediction design optimized using PSO procedure outperforms the LS SVM design. In conclusion, the predictions design on the basis of PSO optimized LS SVM is better appropriate for predicting construction costs early in the building process and has strong guiding importance for the cost of construction.Povzetek: Raziskava predlaga dinamično ocenjevanje stroškov obnove projektov z uporabo postopka optimizacije delcev za natančnejše napovedi.

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Section: Related Workmentioning

confidence: 99%

Dynamic Cost Estimation of Reconstruction Project Based on Particle Swarm Optimization Algorithm

Li¹

2023

IJCAI

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“…Quantum and quantum-inspired algorithms have already been used for the railway system's investigation, but rather for the rolling stock rostering [25]. Our approach is based on the job shop problem, and is inspired by the general approach proposed in [21].…”

Section: Existing Approachesmentioning

confidence: 99%

Quantum computing approach to railway dispatching and conflict management optimization on single-track railway lines

Domino,

Koniorczyk,

Krawiec

et al. 2020

Preprint

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We consider a railway dispatching problem: delay and conflict management on a single-track railway line. We examine the issue of train dispatching consequences caused by the arrival of an already delayed train to the segment being considered. This is a computationally hard problem and its solution is needed in a very short time in practice. We introduce a quadratic unconstrained binary optimization (QUBO) model of the problem that is suitable for solving on quantum annealer devices: an emerging alternative computational hardware technology. These offer a scalability of computationally hard problems better than that of classical computers. We provide a proof-of-principle demonstration of applicability through solving selected real-life problems from the Polish railway network. We carry out the actual calculation on the D-Wave 2000Q machine. We also include solutions of our model using classical algorithms for solving QUBO, including those based on tensor networks. These are of potential practical relevance in case of smaller instances and serve as a comparison for understanding the behavior of the actual quantum device.

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Dynamic optimization based on quantum computation-A comprehensive review

Kou,

Zhang,

Pueh Lee

2024

Computers & Structures

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Quantum-inspired immune clonal algorithm for railway empty cars optimization based on revenue management and time efficiency

Cited by 4 publications

References 6 publications

Dynamic Cost Estimation of Reconstruction Project Based on Particle Swarm Optimization Algorithm

Dynamic Cost Estimation of Reconstruction Project Based on Particle Swarm Optimization Algorithm

Quantum computing approach to railway dispatching and conflict management optimization on single-track railway lines

Dynamic optimization based on quantum computation-A comprehensive review

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