Using simulated annealing for determination of the capacity of yard stations in a railway industry

Javadian, Nikbakhsh; Sayarshad, Hamid R.; Najafi, Sajjad

doi:10.1016/j.asoc.2010.06.006

Cited by 17 publications

(9 citation statements)

References 18 publications

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“…If the NCBS is adjacent to a depot station such as blocking section 1 or 5 in the left, then NCBS has the smallest impact on capacity loss of double-track railway line. Different train speeds have different influence on capacity as discussed in [8,9,16]. Based on the above analysis, we can conclude that the smaller the distance between the NCBS and the depot station, the smaller the impact for a NCBS on capacity loss caused by OGT; the closer the distance between the NCBSs with the middle of the blocking zone, the greater the impact for a NCBS on capacity loss caused by OGT.…”

Section: Ncbss Setting Locationmentioning

confidence: 82%

“…Mussone and Calvo [4] and Abril et al [5] put forward an approach to calculate and assess railway system capacity, and Jelaska [6] constructed a railway line capacity planning support model. Also, Genovesi and Ronzino [7] and Lindfeldt [8] analyzed double-track railway line capacity, while Javadian et al [9] and Corriere et al [10] studied railway station capacity by using simulated annealing and logic fuzzy method.…”

Section: Introductionmentioning

confidence: 99%

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Simulating the Effects of Noncrossing Block Sections Setting Rules on Capacity Loss of Double-Track Railway Line due to the Operation of out-of-Gauge Trains

Zhang

Zeng

Lei

et al. 2016

Discrete Dynamics in Nature and Society

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Dispatchers often set noncrossing block sections (NCBSs) for railway out-of-gauge train (OGT) running on double-track railway line for safety reasons. In this paper, we will investigate the best location, length, and number of noncrossing block sections to reduce railway capacity loss due to the operation of OGTs. Firstly, yielding, overtaking, stopping, starting, and other operation rules for OGTs running on double-track railway line were designed, and a simulation model based on cellular automata was further put forward. Then, an assessment model for double-track railway line capacity loss due to the operation of OGTs was set up. Some simulation experiments and the comparisons of these results were further given to achieve the optimal setting of NCBS for OGTs running on double-track railway line. In the case of NCBSs number minus one, capacity loss caused by the operation of OGTs can be reduced up to 15.2% in the upstream direction and 6.3% in the downstream direction. Also, the NCBSs should lie at the nearest block sections (BSs) to depot stations and the NCBSs lengths should be as less as possible.Hindawi Publishing Corporation

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Section: Ncbss Setting Locationmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Simulating the Effects of Noncrossing Block Sections Setting Rules on Capacity Loss of Double-Track Railway Line due to the Operation of out-of-Gauge Trains

Zhang

Zeng

Lei

et al. 2016

Discrete Dynamics in Nature and Society

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show abstract

“…A number of studies take vehicle type differences into account. In the studies of Sayarshad et al (2010), Javadian et al (2011), andVasco andMorabito (2016), vehicle types are divided into two, as vehicles owned by enterprises and vehicles rented from third parties [29,31,47]. Differences in vehicle features are also considered by List et al (2003) and Lee et al (2008) [21,25].…”

Section: Methodsmentioning

confidence: 99%

Modeling Heterogeneous Fleet Vehicle Allocation Problem with Emissions Considerations

Kazanç¹,

Soysal²,

Çi̇men³

2021

TOTJ

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Aims: This study proposes a bi-objective linear integer programming model for heterogeneous fleet VAP with emissions considerations. Profit maximization and emissions minimization objectives are employed to handle economic and environmental sustainability purposes. Background: Our literature survey shows that there is no model for the heterogeneous fleet VAP with emissions considerations that simultaneously consider vehicle heterogeneity, penalty costs for unmet demands, and emissions from transportation operations. Objective: The model is employed to also make several scenario analyses on sustainable freight logistics management to understand the trade-offs among economic and environmental objectives. In freight transportation problems, decision-makers need to be able to maintain profitability and to reduce emissions. Methods: In this study, a bi-objective linear integer programming model is proposed for a heterogeneous fleet Vehicle Allocation Problem (VAP) with emissions considerations encountered in the field of sustainable freight transportation. Results: In the numerical analyses, various practical assumptions that can be confronted by decision-makers in real life are discussed. In each analysis, total profit and emissions amounts are revealed along with several other KPIs. The results of the analyses provided in this study could also be useful in terms of understanding the relations among pillars of sustainability in VAPs. Conclusion: It is thought that the proposed model has the potential to aid decision-making processes in sustainable logistics management. In the base case analyses, the total profit obtained under profit maximization is about nine times higher than that obtained under emissions minimization. When the aim is to minimize emissions, the total emissions are found to be nearly one-tenth of that of profit maximization. Supported by also additional scenario analyses, it can be concluded that it might not economically viable to be environmentally-friendly for companies. Therefore, companies have to be encouraged or forced to take environmentally and socially responsible actions through legislation. The analyses demonstrated that various legislative policies on emissions may affect the transportation plans differently in such vehicle allocation systems.

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“…This algorithm is designed to find a global optimal result faster than other unsophisticated random search methods (Ketabchi, Ataie-Ashtiani 2015;Zhao, Zeng 2006). It works efficiently on a neighbourhood search within solution space, acceptance probability, and inferior solutions to escape from being trapped in a local mini-mum energy state (Javadian et al 2011). Furthermore, the SAA have been proved to be extremely efficient for solving the hard combinatorial optimization problems (Teghem et al 1995;Jahangiri et al 2011).…”

Section: Algorithmmentioning

confidence: 99%

Optimization of Ship Speed and Fleet Deployment Under Carbon Emissions Policies for Container Shipping

Xing

Yang

et al. 2019

Transport

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In this paper, under the consideration of two carbon emissions policies, the issues of optimizing ship speed and fleet deployment for container shipping were addressed. A mixed-integer nonlinear programming model of ship speed and fleet deployment was established with the objective of minimising total weekly operating costs. A simulated annealing algorithm was proposed to solve the problem. An empirical analysis was conducted with the data selected from the benchmark suite. The applicability and effectiveness of the established model and its algorithm are verified by the results. According to the results, two policies of the cap-and-trade programme and the carbon tax can better optimize the results of the ship speed and fleet deployment problem to achieve the goal of reducing carbon emissions. The research remarks in this paper will provide a solution for container shipping companies to make optimized decisions under carbon emissions policies.

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Using simulated annealing for determination of the capacity of yard stations in a railway industry

Cited by 17 publications

References 18 publications

Simulating the Effects of Noncrossing Block Sections Setting Rules on Capacity Loss of Double-Track Railway Line due to the Operation of out-of-Gauge Trains

Simulating the Effects of Noncrossing Block Sections Setting Rules on Capacity Loss of Double-Track Railway Line due to the Operation of out-of-Gauge Trains

Modeling Heterogeneous Fleet Vehicle Allocation Problem with Emissions Considerations

Optimization of Ship Speed and Fleet Deployment Under Carbon Emissions Policies for Container Shipping

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