A hybrid constructive heuristic and simulated annealing for railway crew scheduling

Hanafi, Rosmalina; Kozan, Erhan

doi:10.1016/j.cie.2014.01.002

Cited by 35 publications

(22 citation statements)

References 16 publications

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“…One of the most important parameters that rarely discussed in simulated annealing applications is the initial value of u. Several investigators have used a very high initial value for u (Tran and Tran, 2007;Ouenes and Hartley, 2000;Sun and Schechter, 2014;Hanafi and Kozen, 2014;Rosen and Harmonosky, 2005). However, if the initial value of the temperature-like parameter is chosen too high, then too many bad uphill moves are accepted.…”

Section: Annealing Schedulementioning

confidence: 99%

An improved simulated annealing algorithm in fracture network modeling

Mahmoodpour

Masihi

2016

Journal of Natural Gas Science and Engineering

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Section: Annealing Schedulementioning

confidence: 99%

An improved simulated annealing algorithm in fracture network modeling

Mahmoodpour

Masihi

2016

Journal of Natural Gas Science and Engineering

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“…Moreover, Elizondo et al [13] presented a constructive hybrid method to address the URCSOP, and provided better results with regard to idle time than both the hybrid and greedy methods. Hanafi and Kozan [14] applied a hybrid constructive heuristic with the simulated annealing search algorithm to solve the rail crew scheduling problem.…”

Section: Introductionmentioning

confidence: 99%

Crew Scheduling Considering both Crew Duty Time Difference and Cost on Urban Rail System

Zhou

Yang

Deng

et al. 2016

PROMET

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Urban rail crew scheduling problem is to allocate train services to crews based on a given train timetable while satisfying all the operational and contractual requirements. In this paper, we present a new mathematical programming model with the aim of minimizing both the related costs of crew duty and the variance of duty time spreads. In addition to iincorporating the commonly encountered crew scheduling constraints, it also takes into consideration the constraint of arranging crews having a meal in the specific meal period of one day rather than after a minimum continual service time. The proposed model is solved by an ant colony algorithm which is built based on the construction of ant travel network and the design of ant travel path choosing strategy. The performances of the model and the algorithm are evaluated by conducting case study on Changsha urban rail. The results indicate that the proposed method can obtain a satisfactory crew schedule for urban rails with a relatively small computational time.

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“…Overcoming the above approaches, hybrid metaheuristics for both single and multiobjective combinatorial optimization problems have received a significant interest from the research community [23,24], and also they have been used in a wide range of real-world applications [25].…”

Section: Introductionmentioning

confidence: 99%

Robust Scheduling for Berth Allocation and Quay Crane Assignment Problem

Rodriguez-Molins

Salido

Barber

2014

Mathematical Problems in Engineering

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Decision makers must face the dynamism and uncertainty of real-world environments when they need to solve the scheduling problems. Different incidences or breakdowns, for example, initial data could change or some resources could become unavailable, may eventually cause the infeasibility of the obtained schedule. To overcome this issue, a robust model and a proactive approach are presented for scheduling problems without any previous knowledge about incidences. This paper is based on proportionally distributing operational buffers among the tasks. In this paper, we consider the berth allocation problem and the quay crane assignment problem as a representative example of scheduling problems. The dynamism and uncertainty are managed by assessing the robustness of the schedules. The robustness is introduced by means of operational buffer times to absorb those unknown incidences or breakdowns. Therefore, this problem becomes a multiobjective combinatorial optimization problem that aims to minimize the total service time, to maximize the buffer times, and to minimize the standard deviation of the buffer times. To this end, a mathematical model and a new hybrid multiobjective metaheuristic is presented and compared with two well-known multiobjective genetic algorithms: NSGAII and SPEA2+.

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A hybrid constructive heuristic and simulated annealing for railway crew scheduling

Cited by 35 publications

References 16 publications

An improved simulated annealing algorithm in fracture network modeling

An improved simulated annealing algorithm in fracture network modeling

Crew Scheduling Considering both Crew Duty Time Difference and Cost on Urban Rail System

Robust Scheduling for Berth Allocation and Quay Crane Assignment Problem

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