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Sequencing Games with Repeated Players

Authors: Peter Borm; Arantza Estévez-Fernández; Arantza Estévez-Fernández; Pedro Calleja; Herbert Hamers;

Sequencing Games with Repeated Players

Abstract

Two classes of one machine sequencing situations are considered in which each job corresponds to exactly one player but a player may have more than one job to be processed, so called RP(repeated player) sequencing situations.In max-RP sequencing situations it is assumed that each player's cost function is linear with respect to the maximum completion time of his jobs, whereas in min-RP sequencing situations the cost functions are linear with respect to the minimum completion times.For both classes, following explicit procedures to go from the initial processing order to an optimal order for the coalition of all players, equal gain splitting rules are defined.It is shown that these rules lead to core elements of the associated RP sequencing games.Moreover, it is seen that min-RP sequencing games are convex.

Keywords

Decision Sciences(all), convexity, cooperative game theory;sequencing;equal gain splitting;core;convexity, equal gain splitting, core, SDG 8 - Decent Work and Economic Growth, sequencing, cooperative game theory; sequencing; equal gain splitting; core; convexity, Management Science and Operations Research, cooperative game theory, jel: jel:C71

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Average
Top 10%
Average
hybrid