A New Cost Allocation Approach on One Machine Sequencing Games

Yan Ping Zhou; Xing Sheng Gu

doi:10.4028/www.scientific.net/AMM.121-126.3731

Paper Titles

A Dual-Population GA Based Visual Identification with Model Matching
p.3708

Research on BLDCM Speed Control System Based on MFNN-PID Control Method
p.3714

A Multi-Hop Grouping Scheme for Assisting Handoff Procedure in Vehicular Networks
p.3719

A Multi-Target Synthetic Assessment Approach for Information Systems Security Risk
p.3726

A New Cost Allocation Approach on One Machine Sequencing Games
p.3731

A Novel Approach of Detector Generation for Real-Valued Negative Selection Algorithm
p.3736

A Novel Improved Web Structure Mining Algorithm
p.3741

A Novel Method Based on Clustering Algorithm and SVM for Anomaly Intrusion Detection of Wireless Sensor Networks
p.3745

A SMS-Based Real-Time Device Monitoring and Abnormality Recovery System for Computer Rooms
p.3750

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 121-126A New Cost Allocation Approach on One Machine...

A New Cost Allocation Approach on One Machine Sequencing Games

Abstract:

One machine sequencing situation is introduced and cooperative games theory is used to allocate cost savings when agents cooperate and gain some cost savings. One machine games is proved to be balanced and have a nonempty core. A new cost allocation, the proportion gain allocation approach, is proposed and proved to give a core allocation for one sequencing games. The results in examples show that the proportion gain allocation approach are fair and reasonable for one machine games.

You might also be interested in these eBooks

Frontiers of Manufacturing and Design Science II

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 121-126)

Pages:

3731-3735

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.121-126.3731

Citation:

Cite this paper

Online since:

October 2011

Authors:

Yan Ping Zhou, Xing Sheng Gu

Keywords:

Cooperative Games Theory, Core of Games, Cost Allocation Approach, One Machine Sequencing

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] S. Tijs and T. Driessen: Management Science Vol. 32 (1986) 1015-1028.

Google Scholar

[2] I. Curiel, G. Pederzoli and S. Tijs: European Journal of Operational Research Vol. 40 (1989), pp.344-351.

DOI: 10.1016/0377-2217(89)90427-x

Google Scholar

[3] I. Curiel, J. Potters and R. Prasad: Operations Research Vol. 42 (1994) , pp.566-568.

Google Scholar

[4] H. Hamers, P. Borm and S. Tijs: Mathematical Programming Vol. 69 (1995) , pp.471-483.

Google Scholar

[5] P. Borm, G. Fiestras and H. Hamers: European Journal of Operational Research Vol. 136 (2002) , pp.616-634.

Google Scholar

[6] H. Hamers, F. Klijn and B. Velzen: Annals of Operations Research Vol. 137 (2005) , pp.161-175.

Google Scholar

[7] V. Velzen: European Journal of Operational Research Vol. 172 (2006) , pp.64-85.

Google Scholar

[8] A. Estevez, M. Mosquera, P. Borm: Journal of Scheduling Vol. 11 (2008) , pp.433-447.

Google Scholar

[9] P. Calleja: Annals of Operations Research Vol. 109 (2002) , pp.265-277.

Google Scholar

[10] Y. P. Zhou and X. S. Gu: CIESC Journal Vol. 61 (2010) , pp.1983-1987, in Chinese.

Google Scholar

[11] I. Curiel: International Journal of Game Theory Vol. 39 (2010) , pp.151-162.

Google Scholar

[12] W. Simth: Naval Research Logistics Quarterly Vol. 3 (1956) , pp.59-66.

Google Scholar

[13] L. Sharply: Annals of Mathematics Studies Vol. 28 (1953) , pp.307-318.

Google Scholar

[14] L. Breton, M.G. Owen and S. Weber: International Journal of Game Theory Vol. 20 (1992) , pp.419-427.

Google Scholar