Journal article
Mixed integer nonlinear programming using interior-point methods
Optimization methods & software, v 26(6), pp 911-931
01 Dec 2011
Abstract
In this paper, we outline an algorithm for solving mixed integer nonlinear programming (MINLP) problems. The approach uses a branch-and-bound framework for handling the integer variables and an infeasible interior-point method for solving the resulting nonlinear subproblems. We report on the details of the implementation, including the efficient pruning of the branch-and-bound tree via equilibrium constraints, warmstart strategies for interior-point methods, and the handling of infeasible subproblems, and present numerical results on a standard problem library. Our goal is to demonstrate the viability of interior-point methods, with suitable modifications, to be used within any MINLP framework, and the numerical results provided are quite encouraging.
Metrics
Details
- Title
- Mixed integer nonlinear programming using interior-point methods
- Creators
- Hande Y Benson - Department of Decision Sciences, Bennett S. LeBow School of Business , Drexel University
- Publication Details
- Optimization methods & software, v 26(6), pp 911-931
- Publisher
- Taylor & Francis
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:000299552900002
- Scopus ID
- 2-s2.0-84857198261
- Other Identifier
- 991014878214704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Software Engineering
- Mathematics, Applied
- Operations Research & Management Science