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Journal of Applied Mathematics
Volume 2015 (2015), Article ID 820430, 15 pages
Research Article

Multisorted Tree-Algebras for Hierarchical Resources Allocation

Department of Computer Science and Educational Technology, Higher Teachers Training College, University of Yaoundé I, Yaoundé, Cameroon

Received 2 December 2014; Revised 13 April 2015; Accepted 29 April 2015

Academic Editor: Robert J. Smith?

Copyright © 2015 Erick Patrick Zobo and Marcel Fouda Ndjodo. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a generic abstract model for the study of disparities between goals and results in hierarchical multiresources allocation systems. In an organization, disparities in resource allocation may occur, when, after comparison of a resource allocation decision with an allocation reference goal or property, some agents have surplus resources to accomplish their tasks, while at the same time other agents have deficits of expected resources. In the real world, these situations are frequently encountered in organizations facing scarcity of resources and/or inefficient management. These disparities can be corrected using allocation decisions, by measuring and reducing gradually such disparities and their related costs, without totally canceling the existing resource distribution. While a lot of research has been carried out in the area of resource allocation, this specific class of problems has not yet been formally studied. The paper exposes the results of an exploratory research study of this class of problems. It identifies the commonalities of the family of hierarchical multiresource allocation systems and proposes the concept of multisorted tree-algebra for the modeling of these problems. The research presented here is not yet an in-depth descriptive research study of the mathematical theory of multisorted tree-algebra, but a formal study on modelling hierarchical multiresource allocation problems.