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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Bibliographic Details
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
Online Access:Get full text
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Summary: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.
Bibliography:SourceType-Scholarly Journals-1
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content type line 14
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2004.06.006