Abstract

Efficient values from Game Theory are used, in order to find out a fair allocation for a scheduling game associated with the problem of scheduling jobs with a common due date. A four person game illustrates the basic ideas and the computational difficulties.

Highlights

  • A machine may process n jobs, J1, J2, Jn, with the completion times p1, p2, pn, all positive numbers

  • Efficient values from Game Theory are used, in order to find out a fair allocation for a scheduling game associated with the problem of scheduling jobs with a common due date

  • This algorithm may be used to find the total penalty for this schedule and to find the total penalty for any minimal deviation corresponding to any subset of jobs

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Summary

A Scheduling Game and Simple Solutions

A machine may process n jobs, J1, J2, , Jn , with the completion times p1, p2, , pn , all positive numbers. J. Kanet solved the problem for the case when the sum of completion times is smaller than, or equal to d , and gave an algorithm for computing a schedule with a minimal deviation. Kanet solved the problem for the case when the sum of completion times is smaller than, or equal to d , and gave an algorithm for computing a schedule with a minimal deviation This algorithm may be used to find the total penalty for this schedule and to find the total penalty for any minimal deviation corresponding to any subset of jobs. To make the paper self contained let us sketch Kanet’s algorithm which will be used in the example shown be- This corresponds to the total deviations of all coalitions, and our problem is to: find out how we should divide fairly w N 28 among the players? The first solution does not seem to show this, while the second seems more fair, we shall see a method below to compare the fairness of the solutions

Individual Penalties
The Cost Least Square Prenucleolus
Conclusions
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