Optimization models for high-speed train unit routing problems

Wang, Ying; Gao, Yuan; Yu, Xiaoyuan; Hansen, Ingo A.; Miao, Jianrui

doi:10.1016/j.cie.2018.02.039

Cited by 17 publications

(9 citation statements)

References 16 publications

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“…Arkhipov et al (2019) used a polynomial algorithm to find the limit of the time schedule of constrained resource projects with the goal of reducing project time. Wang et al (2019) proposed a model for routing high-speed trains in China and provided a generic general model for solving the problems of maintenance of fast trains with the aim of reducing the repair time of these trains with a two-day horizons. They provided a heuristic algorithm to solve their model.…”

Section: Minimizing Makespanmentioning

confidence: 99%

A Multi-Objective Scheduling Algorithm for Multi-Mode Resource Constrained Projects in the Presence of Uncertain Resource Availability

Pouya

Delgoshaei

Ali

2021

BJO&PM

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Goal:The issue of resource allocation is a major concern for project engineers in the scheduling process of a project. Resources over-allocation are often seen in practice after the scheduling of a project, which makes scheduling unhelpful. Modifying an over-allocated schedule is very complicated and requires a lot of effort and time. Besides, during the scheduling process of resource-constrained projects in the constructing companies, managers should concern more than one objective at the same time. This research aims to propose a new heuristic algorithm for minimizing project completion time, cost or maximizing quality of execution of activities simultaneously while multi-mode activities are taken into consideration.Design / Methodology / Approach: In this research, a new heuristic method is proposed for solving multiobjective scheduling problem for multi-mode resource constrained project scheduling problems (MRCPSPs) where the aim is maximizing the net present value (NPV) of project, minimize completion time and maximize the quality of executing activities simultaneously and along with emerging the uncertainty of resources availability and activity durations. The proposed method is then coded by Matlab® 2016. Results:The outcomes of solving small, medium and large scale case studies, the following results achieved: (i) the algorithm could solve all problems in different circumstances with no difficulties; (ii) the large scale problems (with 200 activities, 20 resources and 3 execution modes for each activity) could be solved in 4.43 seconds. (iii) in none of the studied cases over-allocation problem. The proposed method can be considered among the fastest scheduling algorithms found in the literature. In addition, it is found that makespan, NPV and quality have co-relation must be taken into consideration during the scheduling process. Limitations of the investigation:The main limitations of this research is that it only covers resource constrained project scheduling. Moreover, risk factors associated with the objectives of this research have yet to be addressed in future research studies. Practical implications:The performance of the algorithm is validated by using 24 series of dataset that are found in the literature. In order to verify its performance in real practice, it has been applied for a part of a construction project in Malaysia. The outcomes indicated that the algorithm scheduled the problem with 23 activities, 5 constrained resources and 2 execution modes in less than a second and with no over-allocations. The proposed multi-objective algorithm allows the project managers to consider NPV, completion time and quality of activities while scheduling a multi-mode project. In practice, this algorithm can provide a better atmosphere for managers while they aim to consider more than one objective during the scheduling process.Originality / Value: The proposed algorithm is original and can be of great value for future studies and managers in preventing resource over-allocation during the scheduling of mul...

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Section: Minimizing Makespanmentioning

confidence: 99%

A Multi-Objective Scheduling Algorithm for Multi-Mode Resource Constrained Projects in the Presence of Uncertain Resource Availability

Pouya

Delgoshaei

Ali

2021

BJO&PM

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“…Maróti and Kroon [18] proposed an integer programming model with the consideration of maintenance constraint, and they designed a heuristic algorithm to solve the model and obtain a feasible solution. Wang et al [19] used the big M method to formulate the accumulated train-sets' running distances and running time, which is the most intractable part in the trainset utilization problem. To improve the model's solvability, a strategy is proposed to reduce the scale of the connection network.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimizing Train-Set Circulation Plan in High-Speed Railway Networks Using Genetic Algorithm

Wang

Yan

2019

Journal of Advanced Transportation

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As a sustainable transportation mode, high-speed railway (HSR) has been developing rapidly during the past decade in China. With the formation of dense HSR network, how to improve the utilization efficiency of train-sets (the carrying tools of HSR) has been a new research hotspot. Moreover, the emergence of railway transportation hubs has brought great challenges to the traditional train-sets’ utilization mode. Thus, in this paper, we address the issue of train-sets’ utilization problem with the consideration of railway transportation hubs, which consists of finding an optimal Train-set Circulation Plan (TCP) to complete trip tasks in a given Train Diagram (TD). An integer programming TCP model is established to optimize the train-set utilization scheme, aiming to obtain the one-to-one correspondence relationship among sets of train-sets, trip tasks, and maintenances. A genetic algorithm (GA) is designed to solve the model. A case study based on Nanjing and Shanghai HSR transportation hubs is made to demonstrate the practical significance of the proposed method. The results show that a more efficient TCP can be formulated by introducing train-sets being dispatched among different stations in the same hub.

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“…Xu et al [21] proposed a mathematical model for the train routing and timetabling problem with switchable scheduling rules. Based on a connection network, Wang et al [22] proposed a general train unit routing model and then proposed a strategy to reduce the scale of the connection network. Samà et al [23] proposed an integer linear programming model and then designed an algorithm inspired by ant colonies' behavior to solve the real-time train routing selection problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimizing the Paths of Trains Formed at the Loading Area in a Multi-loop Rail Network

Lin

Zhao

2019

Symmetry

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Each loop in a multi-loop rail network consists of two segments, both of which have roughly the same conditions and mileage and are approximately symmetrical. This paper is devoted to optimizing the paths of trains formed at the loading area in a multi-loop rail network. To attain this goal, three different situations are analyzed, and two models are proposed for networks with adequate and inadequate capabilities. Computational experiments are also carried out using the commercial software Lingo, with the branch and bound algorithm. The results show that the models can achieve the same solution with different solution times. To solve the problem of path selection for large-scale train flows, a genetic algorithm is also designed and proves to perform well in a set of computational experiments.

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Optimization models for high-speed train unit routing problems

Cited by 17 publications

References 16 publications

A Multi-Objective Scheduling Algorithm for Multi-Mode Resource Constrained Projects in the Presence of Uncertain Resource Availability

A Multi-Objective Scheduling Algorithm for Multi-Mode Resource Constrained Projects in the Presence of Uncertain Resource Availability

Optimizing Train-Set Circulation Plan in High-Speed Railway Networks Using Genetic Algorithm

Optimizing the Paths of Trains Formed at the Loading Area in a Multi-loop Rail Network

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