New Model for the Railway Network Design Problem

Seyedvakili, S. Alireza; Azadani, S. Masoud Nasr; Zakeri, Jabbar Ali; Shafahi, Yousef; Karimi, M.

doi:10.1061/jtepbs.0000180

Cited by 6 publications

(2 citation statements)

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“…Therefore, properly selecting railway plans helps to properly plan the transportation sector and the correct orientation in the country's development, increases the effectiveness of railway networks, and maximizes social and financial benefits. The railway planning problem can be divided into six subgroups: (i) railway network design problem (RNDP), (ii) crew scheduling problem, (iii) rolling stock assignment, (iv) train routing problem, (v) timetabling problem [3], and (vi) line planning problem [4].…”

Section: Introductionmentioning

confidence: 99%

“…They considered and minimized the total cost, including construction costs, fleet purchase costs, train operational costs, and personnel costs. Syedvakili et al [4] developed a mixed-integer model for designing a railway network from the government's viewpoint. The model made decisions such as constructing a new line or improving the existing line, and the objective function was to minimize the total costs.…”

Section: Introductionmentioning

confidence: 99%

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A Robust Optimization Model for Multi-Period Railway Network Design Problem Considering Economic Aspects and Environmental Impact

et al. 2023

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The railway network design problem is one of the critical issues in the transportation sector due to its significance and variety of necessary applications. The major issue of this field relates to the decision of whether to increase the railways’ capacity or construct a new route to meet demand. Although the budget is a great concern of the managers for making such a decision, environmental factors should be necessarily included in the decision-making process. Therefore, this research proposes a novel robust bi-objective mixed-integer linear programming (MILP) model to simultaneously minimize the total cost and environmental impact under uncertain conditions and within a given time horizon. The proposed problem addresses strategic and operational decisions through railway project selection and product flow determination. To deal with the bi-objectiveness of the model and tackle the complexity of the problem, a nondominated sorting genetic algorithm (NSGA-II) is employed. The proposed NSGA-II could reach near-optimal Pareto solutions in a reasonable solution time and showed a reliable performance for being employed in large-sized instances. It also indicates that the proposed NSGA-II can be utilized for solving large-sized samples in a very short time.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%