A Simheuristic approach to the vehicle ferry revenue management problem
A Simheuristic approach to the vehicle ferry revenue management problem
We propose a Simheuristic approach to the vehicle ferry revenue management problem, where the aim is to maximize the revenue by varying the prices charged to different vehicle types, each occupying a different amount of deck space. Customers arrive and purchase tickets according to their vehicle type and their willingness-to-pay, which varies over time. The optimization problem can be solved using dynamic programming but the possible states in the selling season are the set of all feasible vehicle mixes that fit onto the ferry. This makes the problem intractable as the number of vehicle types increases. We propose a state space reduction, which uses a vehicle ferry loading simulator to map each vehicle mix to a remaining-space state. This reduces the state space of the dynamic program, enabling it to be solved rapidly. We present simulations of the selling season using this reduced state space to validate the method.
2335-2346
Bayliss, Christopher
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Bennell, Julia M.
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Currie, Christine S.M.
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Martinez-Sykora, Antonio
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So, Mee
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December 2016
Bayliss, Christopher
5fb04968-5cbf-40d8-84b0-02e8c7e94a59
Bennell, Julia M.
38d924bc-c870-4641-9448-1ac8dd663a30
Currie, Christine S.M.
dcfd0972-1b42-4fac-8a67-0258cfdeb55a
Martinez-Sykora, Antonio
2f9989e1-7860-4163-996c-b1e6f21d5bed
So, Mee
c6922ccf-547b-485e-8b74-a9271e6225a2
Bayliss, Christopher, Bennell, Julia M., Currie, Christine S.M., Martinez-Sykora, Antonio and So, Mee
(2016)
A Simheuristic approach to the vehicle ferry revenue management problem.
In 2016 Winter Simulation Conference (WSC).
IEEE.
.
(doi:10.1109/WSC.2016.7822274).
Record type:
Conference or Workshop Item
(Paper)
Abstract
We propose a Simheuristic approach to the vehicle ferry revenue management problem, where the aim is to maximize the revenue by varying the prices charged to different vehicle types, each occupying a different amount of deck space. Customers arrive and purchase tickets according to their vehicle type and their willingness-to-pay, which varies over time. The optimization problem can be solved using dynamic programming but the possible states in the selling season are the set of all feasible vehicle mixes that fit onto the ferry. This makes the problem intractable as the number of vehicle types increases. We propose a state space reduction, which uses a vehicle ferry loading simulator to map each vehicle mix to a remaining-space state. This reduces the state space of the dynamic program, enabling it to be solved rapidly. We present simulations of the selling season using this reduced state space to validate the method.
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Accepted/In Press date: 31 August 2016
Published date: December 2016
Venue - Dates:
2016 Winter Simulation Conference (WSC), , Washington D.C., United States, 2016-12-11 - 2016-12-14
Organisations:
Digital and Data Driven Marketing, Decision Analytics & Risk, Operational Research
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Local EPrints ID: 406302
URI: http://eprints.soton.ac.uk/id/eprint/406302
PURE UUID: 2dda9d1c-5b6b-4383-9845-14c9dae34955
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Date deposited: 10 Mar 2017 10:44
Last modified: 16 Mar 2024 04:08
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Author:
Julia M. Bennell
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