Solving railroad blocking problem using ant colony optimization algorithm

Yaghini, Masoud; Foroughi, Amir; Nadjari, Behnam

doi:10.1016/j.apm.2011.05.018

Cited by 40 publications

(18 citation statements)

References 21 publications

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“…Yaghini et al [3] presented a metaheuristic algorithm based on ant colony optimization for solving the RBP. To evaluate the quality of solutions and the algorithm efficiency, the results on several test problems are compared with those of CPLEX software.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The physical network of Iran Railways [3] Suppose that the cost of link (i,j) is c ij , then Eq. 20 to 23 are applied to create fuzzy costs [27] Yaghini et al [3] proposed the RBP model without considering fuzzy costs for the Iranian railway. They solved the RBP by ant colony optimization algorithm.…”

Section: A Case Study Of Iran Railwaysmentioning

confidence: 99%

“…The objective of RBP is to minimize the total travel distance of the shipments. More explanation about the RBP can find in Yaghini et al [3]. The RBP is defined in a physical rail network.…”

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confidence: 99%

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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%

Section: A Case Study Of Iran Railwaysmentioning

confidence: 99%

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

Yaghini

Momeni

Sarmadi

et al. 2015

Applied Mathematical Modelling

Self Cite

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“…Some unique objectives considered in the timetabling include minimizing makespan [8], minimizing the maximum duration between consecutive train arriving at a station [9], minimizing the cost of train delay and energy consumption [10,11], minimizing the number of trains [12], maximizing company profits [13,14], and minimizing train travel time [15].…”

Section: Literature Reviewmentioning

confidence: 99%

A simulated annealing algorithm for first train transfer problem in urban railway networks

Kang

Zhu

2016

Applied Mathematical Modelling

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a b s t r a c tPassengers often have to transfer between different subway lines to reach their destinations. Time coordination of first trains between feeder and connecting lines plays an important role in reducing passenger transfer waiting time. This paper addresses the first train synchronization problem, and proposes a first train coordination model which aims at minimizing total passenger transfer waiting time. Taking into account the specification of the first train problem, we use mixed-integer variables to enable the correct calculation of the waiting time for the ''first available'' train at each transfer station. In addition, we develop a simulated annealing algorithm to deal with a case study of the Beijing subway network. Results indicate that the proposed approach reduces the passenger waiting time from 705.1 min of the original first train timetable to 567.42 min of the scheduled one.

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“…Initially, this algorithm was used to solve single objective problems based on the traveling salesman problem (TSP). However, recently it has been applied to combinatorial optimization problems such as distribution Journal of Advanced Transportation 5 scheduling problem, vehicle routing problem, and railroad blocking problem, among other applications [34][35][36][37][38]. ACO has been applied to transportation systems optimization, but these works have been oriented to find optimal signal setting in function of traffic demand [39][40][41].…”

Section: Ant Colony Optimizationmentioning

confidence: 99%

Design and Evaluation of a Mathematical Optimization Model for Traffic Signal Plan Transition Based on Social Cost Function

Peñabaena‐Niebles

Cantillo

Moura

et al. 2017

Journal of Advanced Transportation

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Signal plan transition is the process of changing from one timing plan to another. It begins when the first intersection starts adjusting signal timing plans and ends when the last intersection completes adjusting signal timing plans. The transition between signal timing plans is required because traffic patterns change during the day. Therefore, it is necessary to modify signal timing parameters offset, phase split, and cycle length for different expectations of traffic volume. This paper presents an alternative and new mathematical model to enhance the performance of traffic signals coordination at intersections during the transition phase. This model is oriented to describe the transition regarding coordination parameters in all intersections of an arterial road for minimizing the social cost during the transition phase expressed in function of costs due to delays, fuel consumption, and air emissions. An ant colony algorithm was designed, coded, and simulated to find the optimal transition parameters using available data. The model was evaluated based on its ability to minimize social costs during the transition period. Results showed that the proposed method performs better than traditional ones.

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Solving railroad blocking problem using ant colony optimization algorithm

Cited by 40 publications

References 21 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

A simulated annealing algorithm for first train transfer problem in urban railway networks

Design and Evaluation of a Mathematical Optimization Model for Traffic Signal Plan Transition Based on Social Cost Function

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