Processing games with restricted capacities

Annals of Operations Research, 2008

This paper introduces processing problems with shared interest as an extension of processing situations with restricted capacities (Meertens, M., et al., Processing games with restricted capacities, 2004). Next to an individual capacity to handle jobs, each player now may have interest in the completion of more than one job, and the degrees of interest may vary among players. By cooperating the players can bundle their capacities and follow an optimal processing scheme to minimize total joint costs. The resulting cost allocation problem is analyzed by considering an associated cooperative cost game. An explicit core allocation of this game is provided.

2004

This paper considers one machine job scheduling situations or sequencing problems, where clients can have more than a single job to be processed in order to get a final output. Moreover, a job can be of interest for different players. This means that one of the main assumptions in classic sequencing problems is dropped: the one to one correspondence between clients and jobs. It is shown that the corresponding cooperative games are balanced for specific types of cost criteria.

Artificial Intelligence, 2006

International Journal of Game Theory

ETFA2011, 2011

Artificial Intelligence, 2010

Synthesis Lectures on Artificial Intelligence and Machine Learning, 2011

We present the problem of tasks allocation in its general form as a non-cooperative game between players. For this game, we give the Nash equilibrium structure and on the basis of this structure, we draw a distributed tasks allocation algorithm that can find this equilibrium.