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The P-norm surrogate-constraint algorithm for polynomial zero-one programming.

by Wang Jun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 82-86). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- The polynomial zero-one programming problem --- p.2 / Chapter 1.3 --- Motivation --- p.3 / Chapter 1.4 --- Thesis outline --- p.4 / Chapter 2 --- Literature Survey --- p.6 / Chapter 2.1 --- Lawler and Bell's method --- p.7 / Chapter 2.2 --- The covering relaxation algorithm for polynomial zero-one pro- gramming --- p.8 / Chapter 2.3 --- The method of reducing polynomial integer problems to linear zero- one problems --- p.9 / Chapter 2.4 --- Pseudo-boolean programming --- p.11 / Chapter 2.5 --- The Balasian-based algorithm for polynomial zero-one programming --- p.12 / Chapter 2.6 --- The hybrid algorithm for polynomial zero-one programming --- p.12 / Chapter 3 --- The Balasian-based Algorithm --- p.14 / Chapter 3.1 --- The additive algorithm for linear zero-one programming --- p.15 / Chapter 3.2 --- Some notations and definitions referred to the Balasian-based al- gorithm --- p.17 / Chapter 3.3 --- Identification of all the feasible solutions to the master problem --- p.18 / Chapter 3.4 --- Consistency check of the feasible partial solutions --- p.19 / Chapter 4 --- The p-norm Surrogate Constraint Method --- p.21 / Chapter 4.1 --- Introduction --- p.21 / Chapter 4.2 --- Numerical example --- p.23 / Chapter 5 --- The P-norm Surrogate-constraint Algorithm --- p.26 / Chapter 5.1 --- Main ideas --- p.26 / Chapter 5.2 --- The standard form of the polynomial zero-one programming problem --- p.27 / Chapter 5.3 --- Definitions and notations --- p.29 / Chapter 5.3.1 --- Partial solution in x --- p.29 / Chapter 5.3.2 --- Free term --- p.29 / Chapter 5.3.3 --- Completion --- p.29 / Chapter 5.3.4 --- Feasible partial solution --- p.30 / Chapter 5.3.5 --- Consistent partial solution --- p.30 / Chapter 5.3.6 --- Partial solution in y --- p.30 / Chapter 5.3.7 --- Free variable --- p.31 / Chapter 5.3.8 --- Augmented solution in x --- p.31 / Chapter 5.4 --- Solution concepts --- p.33 / Chapter 5.4.1 --- Fathoming --- p.33 / Chapter 5.4.2 --- Backtracks --- p.41 / Chapter 5.4.3 --- Determination of the optimal solution in y --- p.42 / Chapter 5.5 --- Solution algorithm --- p.42 / Chapter 6 --- Numerical Examples --- p.46 / Chapter 6.1 --- Solution process by the new algorithm --- p.46 / Chapter 6.1.1 --- Example 5 --- p.46 / Chapter 6.1.2 --- Example 6 --- p.57 / Chapter 6.2 --- Solution process by the Balasian-based algorithm --- p.61 / Chapter 6.3 --- Comparison between the p-norm surrogate constraint algorithm and the Balasian-based algorithm --- p.71 / Chapter 7 --- Application to the Set Covering Problem --- p.74 / Chapter 7.1 --- The set covering problem --- p.74 / Chapter 7.2 --- Solving the set covering problem by using the new algorithm . .。 --- p.75 / Chapter 8 --- Conclusions and Future Work --- p.80 / Bibliography --- p.82

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_322614
Date January 1999
ContributorsWang, Jun., Chinese University of Hong Kong Graduate School. Division of Systems Engineering and Engineering Management.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, ix, 86 leaves ; 30 cm.
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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