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**Harvard**

Sharifyazdi, M., Dekker, R. och Mulder, J. (2011) *Optimization of Buffer Times and Recovery Actions in Liner Shipping Networks*.

** BibTeX **

@unpublished{

Sharifyazdi2011,

author={Sharifyazdi, Mehdi and Dekker, Rommert and Mulder, Judith},

title={Optimization of Buffer Times and Recovery Actions in Liner Shipping Networks},

abstract={The main goal of this paper is to develop a method to help liner shipping networks to cope with delay and its costs. To do so, the paper studies two types of policies to prevent and recover delay, firstly, to assign buffer times to different stages of a trip in the scheduling and secondly, to perform recovery actions during the trip in case delay occurs. A mathematical optimization model is formulated to determine how these policies should be implemented in order to minimize the total cost of the trip including delay cost and cost of recovery actions. The model formulates delay as a stochastic phenomenon depending on exogenous factors, recovery actions and buffer times. To solve the model, the paper develops a two-phase global optimization algorithm based on stochastic dynamic programming. The first phase tries to find a good feasible solution for the problem and the second phase finds the optimal solution by a branch and bound algorithm. Finally, the algorithm is tested on a real problem and finds its optimal solution in a short time.},

year={2011},

keywords={Liner Shipping, Delay Management, Dynamic Programming, Time Tabling, Scheduling, Recovery Actions, Buffer Time},

}

** RefWorks **

RT Unpublished Material

SR Print

ID 152577

A1 Sharifyazdi, Mehdi

A1 Dekker, Rommert

A1 Mulder, Judith

T1 Optimization of Buffer Times and Recovery Actions in Liner Shipping Networks

YR 2011

AB The main goal of this paper is to develop a method to help liner shipping networks to cope with delay and its costs. To do so, the paper studies two types of policies to prevent and recover delay, firstly, to assign buffer times to different stages of a trip in the scheduling and secondly, to perform recovery actions during the trip in case delay occurs. A mathematical optimization model is formulated to determine how these policies should be implemented in order to minimize the total cost of the trip including delay cost and cost of recovery actions. The model formulates delay as a stochastic phenomenon depending on exogenous factors, recovery actions and buffer times. To solve the model, the paper develops a two-phase global optimization algorithm based on stochastic dynamic programming. The first phase tries to find a good feasible solution for the problem and the second phase finds the optimal solution by a branch and bound algorithm. Finally, the algorithm is tested on a real problem and finds its optimal solution in a short time.

LA eng

OL 30