Global optimization of mixed-integer nonlinear programs: A theoretical and computational study

成果类型:
Article
署名作者:
Tawarmalani, M; Sahinidis, NV
署名单位:
Purdue University System; Purdue University; University of Illinois System; University of Illinois Urbana-Champaign
刊物名称:
MATHEMATICAL PROGRAMMING
ISSN/ISSBN:
0025-5610
DOI:
10.1007/s10107-003-0467-6
发表日期:
2004
页码:
563-591
关键词:
bound algorithm branch approximation minimization
摘要:
This work addresses the development of an efficient solution strategy for obtaining global optima of continuous. integer. and mixed-integer nonlinear programs. Towards this end, we develop novel relaxation schemes, range reduction tests, and branching strategies which we incorporate into the prototypical branch-and-bound algorithm. In the theoretical/algorithmic part of the paper. we begin by developing novel strategies for constructing linear relaxations of mixed-integer nonlinear programs and prove that these relaxations enjoy quadratic convergence properties, We then use Lagrangian/linear programming duality to develop a unifying theory of domain reduction strategies as a consequence of which we derive many range reduction strategies currently used in nonlinear programming and integer linear programming. This theory leads to new range reduction schemes. including a learning heuristic that improves initial branching decisions by relaying data across siblings in a branch-and-bound tree. Finally, we incorporate these relaxation and reduction strategies in a branch-and-bound algorithm that incorporates branching strategies that guarantee finiteness for certain classes of continuous global optimization problems. In the computational part of the paper, we describe our implementation discussing, wherever appropriate, the use of suitable data structures and associated algorithms. We present computational experience with bench-mark separable concave quadratic programs, fractional 0-1 programs, and mixed-integer nonlinear programs from applications in synthesis of chemical processes, engineering design, just-in-time manufacturing, and molecular design.
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