Proceedings of the 2019 International Conference on Modeling, Simulation, Optimization and Numerical Techniques (SMONT 2019)

Optimality Conditions for Local Optimal Solutions of Major Constraints Programming

Authors
Xuanwei Zhou
Corresponding Author
Xuanwei Zhou
Available Online April 2019.
DOI
10.2991/smont-19.2019.27How to use a DOI?
Keywords
major constraints programming; local optimal solution; Fritz John condition; Kuhn-Tucker condition
Abstract

Three optimality conditions for local optimal solutions of major constraints programming are studied. By using the representation of major constraints set structure, Fritz John condition of local optimal solution is obtained. Kuhn-Tucker condition of the major constraints local optimal solution under K-T constraint qualification is established. At the same time, a sufficient optimality condition of major constraints local optimal solution under some convexity conditions is given.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2019 International Conference on Modeling, Simulation, Optimization and Numerical Techniques (SMONT 2019)
Series
Advances in Intelligent Systems Research
Publication Date
April 2019
ISBN
10.2991/smont-19.2019.27
ISSN
1951-6851
DOI
10.2991/smont-19.2019.27How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xuanwei Zhou
PY  - 2019/04
DA  - 2019/04
TI  - Optimality Conditions for Local Optimal Solutions of Major Constraints Programming
BT  - Proceedings of the 2019 International Conference on Modeling, Simulation, Optimization and Numerical Techniques (SMONT 2019)
PB  - Atlantis Press
SP  - 121
EP  - 125
SN  - 1951-6851
UR  - https://doi.org/10.2991/smont-19.2019.27
DO  - 10.2991/smont-19.2019.27
ID  - Zhou2019/04
ER  -