A Method for using Mathematical Optimization to Allocate and Reallocate Geographically Distributed, Reconfigureable Resources with Spatial Considerations and Time Windows
Original Publication Date: 2004-Jul-20
Included in the Prior Art Database: 2004-Jul-20
The invention is described in Research Report RJ10301- In this report we formulate a model for the scheduling of reconfigurable resources to meet demand over time, with particular consideration for the potential need to reschedule and reconfigure the resources as new demands arise. This is accomplished in the framework of "continual optimization" using dynamic column and constraint generation schemes to accommodate the enormous number of possible variables and constraints.
RJ 10301 Declassified (W0402-016) February 4, 2004 Mathematics
IBM Research Report
A Method for Using Mathematical Optimization to Allocate and Reallocate Geographically Distributed, Reconfigureable Resources with Spatial Considerations and Time Windows
John A. Tomlin
IBM Research Division Almaden Research Center 650 Harry Road San Jose, CA 95120-6099
Mary E. Helander, Brenda L. Dietrich, J. P. Fasano, Baruch M. Schieber
IBM Research Division Thomas J. Watson Research Center P.O. Box 218 Yorktown Heights, NY 10598
Research Division Almaden - Austin - Beijing - Haifa - India - T. J. Watson - Tokyo - Zurich
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A METHOD FOR USING MATHEMATICAL OPTIMIZATION TO ALLOCATE AND REALLOCATE GEOGRAPHICALLY DISTRIBUTED RECONFIGUREABLE RESOURCES WITH SPATIAL
CONSIDERATIONS AND TIME WINDOWS
John A Tomlin
IBM Research Division Almaden Research Center San Jose CA e mail tomlin almaden ibm com
Mary E Helander Brenda L Dietrich J P Fasano Baruch M Schieber
IBM Research Division Thomas J Watson Research Center Yorktown Heights NY e mail helandm dietric jpfasano sbar us ibm com
ABSTRACT In this report we formulate a model for the scheduling of recon gurable resources to meet demand over time with particular consideration for the potential need to reschedule and recon gure the resources as new demands arise This is accomplished in the framework of continual optimization using dynamic column and constraint generation schemes to accommodate the enormous number of possible variables and constraints
Keywords recon gurable facilities scheduling integer programming continual optimiza tion column generation constraint generation
The scheduling of scarce resources over time to meet demand in some optimal sense e g minimum cost or maximum pro t is a problem which has been at the forefront of Operations Research and Mathematical Programming in particular since the founding of the eld Examples such as job shop scheduling are ubiquitous in the literature Another class of examples is the scheduling of facilities such as classrooms to accommodate a given number of classes of...