Reliability redundancy allocation: An improved realization for nonconvex nonlinear programming problems

The redundancy allocation problem, which seeks to find the optimal allocation of redundancy that maximizes system reliability, is one of the representative problems in reliability optimization. The problem can be formulated as a nonconvex integer nonlinear programming problem. This paper presents an...

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Published in:	European journal of operational research Vol. 171; no. 1; pp. 24 - 38
Main Authors:	Ha, Chunghun, Kuo, Way
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 16.05.2006 Elsevier Elsevier Sequoia S.A
Series:	European Journal of Operational Research
Subjects:	Allocations Applied sciences Branch & bound algorithms Branch-and-bound Exact sciences and technology Integer programming Mathematical programming Operational research and scientific management Operational research. Management science Operations research Optimization Redundancy Redundancy allocation Reliability Reliability theory. Replacement problems Studies Integer programming Branch-and-bound Reliability Redundancy allocation Monotonic function Coherent system Separability Non convex programming Branch and bound method Redundancy Non linear programming System reliability Optimization Optimal allocation Objective function
ISSN:	0377-2217, 1872-6860
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Abstract	The redundancy allocation problem, which seeks to find the optimal allocation of redundancy that maximizes system reliability, is one of the representative problems in reliability optimization. The problem can be formulated as a nonconvex integer nonlinear programming problem. This paper presents an efficient branch-and-bound approach to solve this problem, where the considered system is coherent, that is, the objective and constraint functions have monotonic increasing properties. The proposed method is based primarily on a search space elimination of disjoint sets in a solution space that does not require any relaxation of branched subproblems. The main advantage of the proposed method is flexibility (i.e., it does not rely on any assumptions of linearity, separability, single constraint, or convexity) which make the method adaptive to various applications. Numerical experiments demonstrate that the method is superior to the existing exact algorithms for redundancy allocation problems in terms of computation time.
AbstractList	The redundancy allocation problem, which seeks to find the optimal allocation of redundancy that maximizes system reliability, is one of the representative problems in reliability optimization. The problem can be formulated as a nonconvex integer nonlinear programming problem. This paper presents an efficient branch-and-bound approach to solve this problem, where the considered system is coherent, that is, the objective and constraint functions have monotonic increasing properties. The proposed method is based primarily on a search space elimination of disjoint sets in a solution space that does not require any relaxation of branched subproblems. The main advantage of the proposed method is flexibility (i.e., it does not rely on any assumptions of linearity, separability, single constraint, or convexity) which make the method adaptive to various applications. Numerical experiments demonstrate that the method is superior to the existing exact algorithms for redundancy allocation problems in terms of computation time. The redundancy allocation problem, which seeks to find the optimal allocation of redundancy that maximizes system reliability, is one of the representative problems in reliability optimization. The problem can be formulated as a nonconvex integer nonlinear programming problem. This paper presents an efficient branch-and-bound approach to solve this problem, where the considered system is coherent, that is, the objective and constraint functions have monotonic increasing properties. The proposed method is based primarily on a search space elimination of disjoint sets in a solution space that does not require any relaxation of branched subproblems. The main advantage of the proposed method is flexibility (i.e., it does not rely on any assumptions of linearity, separability, single constraint, or convexity) which make the method adaptive to various applications. Numerical experiments demonstrate that the method is superior to the existing exact algorithms for redundancy allocation problems in terms of computation time. [PUBLICATION ABSTRACT]
Author	Kuo, Way Ha, Chunghun
Author_xml	– sequence: 1 givenname: Chunghun surname: Ha fullname: Ha, Chunghun email: chriver58@yahoo.com organization: Department of Industrial Engineering, Texas A&M University, College Station, TX 77843-3131, USA – sequence: 2 givenname: Way surname: Kuo fullname: Kuo, Way email: way@utk.edu organization: College of Engineering, University of Tennessee, 124 Perkins Hall, Knoxville, TN 37996-2000, USA
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SubjectTerms	Allocations Applied sciences Branch & bound algorithms Branch-and-bound Exact sciences and technology Integer programming Mathematical programming Operational research and scientific management Operational research. Management science Operations research Optimization Redundancy Redundancy allocation Reliability Reliability theory. Replacement problems Studies
Title	Reliability redundancy allocation: An improved realization for nonconvex nonlinear programming problems
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