Ein allgemeines Dekompositionsverfahren fuer lineare Optimierungsprobleme
A General Decomposition Algorithm for Linear Optimization Problems
Hergen H. Heinemann
MPRA Paper from University Library of Munich, Germany
Abstract:
A Really GENERAL Decomposition Algorithm for Very Large Linear Optimization Problems Proven theory as Regards Optimality and Finality Advantageous for very large problems with a rather small percentage of real variables in the optimal solution - Simplex method is used as a calculating sub-routine - NO SPECIAL STRUCTURE OF MATRIX REQUIRED - Method applicable without change for non-structures as well as for any and all structures of matrix. Maximum necessary problem size to be calculated with simplex method procedure: a bit more than a matrix of optimal-solution original variables and optimal solution restrictions - single-stage or double-stage decomposition possible - parametric-programming-similar re-calculations possible. For consultancy on slight extensions in theory as well as on important extensions in calculation tactics you may contact Dr. Hergen Heinemann: Hergen.Heinemann"et"alumni.insead.edu Detailed ABSTRACT of Theory (1) From the total problem matrix (TPM) partial problems (PP) are taken arbitrarily, but every variable should be represented in at least one of them. (2) PPA´s are equipped with suitable functions for optimization and are optimized with the simplex method procedure. (3) The optimized solutions of the PPA´s serve to obtain variables for an auxiliary problem (AP), which is then optimized to reflect an optimal combination of the optimized PP`s. (4) With the optimal dual values of the AP the actual values for every variable of the to-be-optimized function of the TPM are calculated. (5) With the actual values for every variable of the to-be-optimized function of the TPM a test is done to check whether the optimal solution of the TPM is already reached. (6) Is the optimum solution of the TPM reached, then the algorithm is at the end. If not, the algorithm continues with item (2) above with a new set of variables and using the actual values of the variables of the to-be-optimized function as per item (3), starting a new cycle of the algorithm. Original copy may be available at: Titel: Ein allgemeines Dekompositionsverfahren fuer lineare Optimierungsprobleme (in English: A General Decomposition Algorithm for Linear Optimization Problems) ( To obtain a copy of this operations research on linear programming paper e-mail to Technische Universitaet, Braunschweig:) fernleihe@tu-bs.de Author: Heinemann, Hergen Published: 1971 No. of pages: III, 80 S. ; 8º Doctoral Degree Paper: Saarbruecken, University, Diss., 1971 Signature: 2400-3106 / Tiefmagazin, 2. UG
Keywords: general decomposition algorithm; allgemeiner Dekompositionsalgorithmus; linear optimization problems; lineare Optimierungsprobleme; Dekomposition; linear programming; lineare Programmierung; Operations Research; very large linear optimizationproblems; Dekompositionsalgorithmus fuer lineare Optimierungsprobleme; Dr. Hergen Heinemann; Endlichkeitsbeweis; optimality; finality; Optimalitätsbeweis (search for similar items in EconPapers)
JEL-codes: C02 C61 C65 (search for similar items in EconPapers)
Date: 1971
References: View references in EconPapers View complete reference list from CitEc
Citations:
Published in Zeitschrift fuer betriebswirtschaftliche Forschung 22 (1970): pp. 302-317
Downloads: (external link)
https://mpra.ub.uni-muenchen.de/28842/3/MPRA_paper_28842.pdf original version (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:28842
Access Statistics for this paper
More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().