Online production planning to maximize the number of on-time orders
Online production planning to maximize the number of on-time orders
We consider a production planning problem with two planning periods. Detailed planning occurs in the first period, when complete information is known about a set of orders that are initially available. An additional set of orders becomes available at the start of the second planning period. The objective is to maximize the number of on-time orders. We derive an upper bound on the competitive ratio of any deterministic online algorithm, relative to the performance of an algorithm with perfect information about the second set of orders. This ratio depends on the relative lengths of the two planning periods. We also describe an efficient algorithm that delivers a solution which asymptotically achieves this upper bound ratio as the number of jobs becomes large.
Online planning, Scheduling, Planning horizons , Competitive analysis
Hall, Nicholas
922324f0-a49b-4d93-ba40-70d4dc163e74
Posner, Marc
086a4841-0229-4492-a73b-9f3028dd46df
Potts, Christopher
58c36fe5-3bcb-4320-a018-509844d4ccff
Hall, Nicholas
922324f0-a49b-4d93-ba40-70d4dc163e74
Posner, Marc
086a4841-0229-4492-a73b-9f3028dd46df
Potts, Christopher
58c36fe5-3bcb-4320-a018-509844d4ccff
Hall, Nicholas, Posner, Marc and Potts, Christopher
(2018)
Online production planning to maximize the number of on-time orders.
Annals of Operations Research.
(doi:10.1007/s10479-018-2928-6).
Abstract
We consider a production planning problem with two planning periods. Detailed planning occurs in the first period, when complete information is known about a set of orders that are initially available. An additional set of orders becomes available at the start of the second planning period. The objective is to maximize the number of on-time orders. We derive an upper bound on the competitive ratio of any deterministic online algorithm, relative to the performance of an algorithm with perfect information about the second set of orders. This ratio depends on the relative lengths of the two planning periods. We also describe an efficient algorithm that delivers a solution which asymptotically achieves this upper bound ratio as the number of jobs becomes large.
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PlanningHorizonsAcceptedAnnOR
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More information
Accepted/In Press date: 30 May 2018
e-pub ahead of print date: 2 July 2018
Keywords:
Online planning, Scheduling, Planning horizons , Competitive analysis
Identifiers
Local EPrints ID: 422682
URI: http://eprints.soton.ac.uk/id/eprint/422682
PURE UUID: b49bf687-b215-46ba-9109-fe8a0088feff
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Date deposited: 30 Jul 2018 16:30
Last modified: 16 Mar 2024 06:54
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Contributors
Author:
Nicholas Hall
Author:
Marc Posner
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