New approaches for solving the block‐to‐train assignment problem

Jha, Krishna C.; Ahuja, Ravindra K.; Şahin, Güvenç

doi:10.1002/net.20195

Cited by 50 publications

(24 citation statements)

References 27 publications

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“…Yaghini et al [26] proposed a solution method on the basis of genetic algorithm for the RBP, and then evaluated the quality of solutions and algorithm efficiency on several small-size test problems. Jha et al [23] presented an arc-based and a path-based formulation and proposed exact and heuristic algorithms. The combined problem of blocking, train routing and makeup is presented by Keaton [17] and a heuristic method based on Lagrangian relaxation is applied to solve it.…”

Section: Literature Reviewmentioning

confidence: 99%

A fuzzy railroad blocking model with genetic algorithm solution approach for Iranian railways

Yaghini

Momeni

Sarmadi

et al. 2015

Applied Mathematical Modelling

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Please cite this article as: M. Yaghini, M. Momeni, M. Sarmadi, M. Seyedabadi, M.M. Khoshraftar, A fuzzy railroad blocking model with genetic algorithm solution approach for Iranian Railways, Appl. Math. Modelling (2014), doi: http://dx. AbstractIn the railway, the fright car classification takes place in the terminals. This classification always imposes a remarkable delay to the movement of the cars from origin to destination. To reduce car handling, it is necessary to group various shipments together with respect to their destination in the railroad blocking plan. In this paper, for the first time, a railroad blocking model with fuzzy travel costs is proposed. In the model, the preferred fuzzy paths are determined by a fuzzy shortest path method. Then, the fuzzy model is transformed into a classic railroad blocking model. The real-life blocking problems are very large with many variables and constraints, and modeling and solving them using commercially available software is very time consuming. Therefore, a solution method based on genetic algorithm is developed. To evaluate the performance of the solution method, several simulated problems are tested and the solutions of genetic algorithm are compared with those of the CPLEX software. The results reveal the algorithm has promising accuracy and computing speed for solving the railroad blocking problem. As a case study, the proposed model for creating the Iranian railway blocking plan is utilized. Iran Railways can significantly diminish the some costs and save the time in delivering the loads.

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Section: Literature Reviewmentioning

confidence: 99%

A fuzzy railroad blocking model with genetic algorithm solution approach for Iranian railways

Yaghini

Momeni

Sarmadi

et al. 2015

Applied Mathematical Modelling

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“…Given a blocking plan and a train schedule, the block-to-train assignment problem determines which trains will transport each block (Jha et al 2008). …”

Section: Locomotive Research Applicationsmentioning

confidence: 99%

Integrated optimization and simulation models for the locomotive refueling system configuration problem

Verschelden¹,

Stamm²,

Easton³

2017

2017 Winter Simulation Conference (WSC)

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Locomotives in the U.S. use over 3 billion gallons of fuel each year and faster refueling can increase rail network capacity without the infrastructure cost associated with new terminals or tracks. This thesis introduces the locomotive refueling system configuration problem (LRSCP), which seeks to improve efficiency in refueling yards through new technologies or policies. This research also creates two new methods to solve LRSCP. Based on experimental results, solving either TRIP or SLIP and incorporating the optimal refueling policy improves railyard operations by 10 to 30%. This impact is statistically significant and increases the capacity of a railyard. Additionally, it impacts other important parameters such as time spent in the yard and the maximum queue for the railyard. Furthermore, there is a significant decrease in wasted time and an improvement to railyard efficiency.Implementing either method should increase a railyard's capacity and significantly increase revenue opportunities.iv

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“…These exponential neighborhoods are obtained by considering, as neighbors, configurations that can be reached by a set or sequence of atomic moves. VLSN algorithms have been successfully applied to a variety of NP-Hard problems such as Vehicle Routing Problems Thompson and Psaraftis, 1993), Capacitated Minimum Spanning Tree (Ahuja et al, 2001(Ahuja et al, , 2003, Exam Timetabling (Abdullah et al, 2007b(Abdullah et al, , 2004(Abdullah et al, , 2007a, the Quadratic Assignment Problem (Deineko and Woeginger, 2000) and Block-to-train Assignment (Jha et al, 2008). VLSN search algorithms behave very well on these applications because there are many constraints that are hard to satisfy.…”

Section: Related Workmentioning

confidence: 99%

A Multistage Very Large-Scale Neighborhood Search for the Vehicle Routing Problem with Soft Time Windows

Mouthuy

Massen

Deville

et al. 2015

Transportation Science

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This paper considers the Vehicle Routing Problem with Soft Time Windows, a challenging routing problem, where customer's time windows may be violated at a certain cost. The Vehicle Routing Problem with Soft Time Windows has a lexicographic objective function, aiming at minimizing first the number of routes, then the number of violated time windows and finally the total routing distance. We present a multi-stage Very Large-Scale Neighborhood search for this problem. Each stage corresponds to a Variable Neighborhood Descent over a parametrizable Very Large-Scale Neighborhood. These neighborhoods contain an exponential number of neighbors, as opposed to classical local search neighborhoods. Often, searching Very Large-Scale Neighborhoods can produce local optima of a higher quality than polynomial-sized neighborhoods. Furthermore we use a sophisticated heuristic to determine service start times allowing to minimize the number of violated time windows. We test our approach on number of different problem types, and compare the results to the relevant state-of-the-art. The experimental results show that our algorithm improves best-known solutions on 53% of the most studied instances. Many of these improvements stem from a reduction of the number of vehicles, a critical objective in Vehicle Routing Problems.

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New approaches for solving the block‐to‐train assignment problem

Cited by 50 publications

References 27 publications

A fuzzy railroad blocking model with genetic algorithm solution approach for Iranian railways

A fuzzy railroad blocking model with genetic algorithm solution approach for Iranian railways

Integrated optimization and simulation models for the locomotive refueling system configuration problem

A Multistage Very Large-Scale Neighborhood Search for the Vehicle Routing Problem with Soft Time Windows

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