Entropy based region reducing genetic algorithm for reliability redundancy allocation in interval environment

Mahapatra, B. S.; Mahapatra, G. S.; Roy, Pratik

doi:10.1016/j.eswa.2014.04.016

Cited by 42 publications

(22 citation statements)

References 24 publications

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“…3 Complexity (8) Conversion switches of the standby system are absolutely reliable, and the conversion is instantaneous. (9) The costs of all the elements are independent uncertain variables, and the weights and volumes of all the elements are independent random variables.…”

Section: Problem Formulation Of An Uncertain Parallel-series Systemmentioning

confidence: 99%

“…Recently, some researchers have addressed reliability optimization designs of some systems by considering interval-valued component reliability in an uncertain environment. Roy et al [9] applied the symmetrical form of interval numbers by interval-valued parametric functional form to evaluate the optimum system reliability and system cost of the redundancy allocation problem. Zhang and Chen [10] investigated an interval multiobjective optimization problem for reliability redundancy allocation of a series-parallel system.…”

Section: Introductionmentioning

confidence: 99%

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Redundancy Optimization of an Uncertain Parallel‐Series System with Warm Standby Elements

Huang

Wang

et al. 2018

Complexity

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The redundancy optimization problem is formulated for an uncertain parallel-series system with warm standby elements. The lifetimes and costs of elements are considered uncertain variables, and the weights and volumes of elements are random variables. The uncertain measure optimization model (UMOM), the uncertain optimistic value optimization model (UOVOM), and the uncertain cost optimization model (UCOM) are developed through reliability maximization, lifetime maximization, and cost minimization, respectively. An efficient simulation optimization algorithm is provided to calculate the objective values and optimal solutions of the UMOM, UOVOM, and UCOM. A numerical example is presented to illustrate the rationality of the models and the feasibility of the optimization algorithm.

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Section: Problem Formulation Of An Uncertain Parallel-series Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Redundancy Optimization of an Uncertain Parallel‐Series System with Warm Standby Elements

Huang

Wang

et al. 2018

Complexity

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“…By incorporating the dual model (26) into the problem (21), and the fact that , the robust counterpart of uncertain , for integer , is as follows. (27) Model (27) has binary variables, continuous variables, and linear constraints.…”

Section: B Binary Linear Equivalent For Csrapmentioning

confidence: 99%

“…In the case of random reliabilities with known statistical means and standard deviations, multi-criteria approaches have been proposed (e.g., [19]- [21]). The interval programming approaches assume that the uncertain data are within intervals with known lower and upper bounds (e.g., see [22]- [27]). …”

Section: Introductionmentioning

confidence: 99%

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The Robust Cold Standby Redundancy Allocation in Series-Parallel Systems With Budgeted Uncertainty

2015

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This paper studies a redundancy allocation problem (RAP) with cold standby strategy in non-repairable series-parallel systems. We assume that the components' reliabilities are uncertain values in a budgeted uncertainty set, with unknown probability distributions. Because the system reliability is a nonlinear function of the components' reliabilities, classical robust optimization approaches cannot be directly applied to construct the robust counterpart of this problem. Therefore, this paper for the first time proposes linear mixed integer programming (MIP) and binary equivalent models for the cold standby RAP; and by exploiting the problem structure, robust counterparts are developed to deal with budgeted uncertainty in this problem. Then, two exact solution methods are proposed: one of them solves a MIP model iteratively in a Benders' decomposition framework, and the other one solves a single binary linear model. The validity and the performance of the proposed approach are tested through a Monte Carlo simulation, and computational results.Index Terms-Budgeted uncertainty, cold standby redundancy allocation, mixed integer nonlinear programming, robust optimization, series-parallel system.

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Entropy based enhanced particle swarm optimization on multi‐objective software reliability modelling for optimal testing resources allocation

Rani¹,

Mahapatra²

2021

Software Testing Verif & Rel

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Summary This paper proposes a generalization of the exponential software reliability model to characterize several factors including fault introduction and time‐varying fault detection rate. The software life cycle is designed based on module structure such as testing effort spent during module testing and detected software faults etc. The resource allocation problem is a critical phase in the testing stage of software reliability modelling. It is required to make decisions for optimal resource allocation among the modules to achieve the desired level of reliability. We formulate a multi‐objective software reliability model of testing resources for a new generalized exponential reliability function to characterizes dynamic allocation of total expected cost and testing effort. An enhanced particle swarm optimization (EPSO) is proposed to maximize software reliability and minimize allocation cost. We perform experiments with randomly generated testing‐resource sets and varying the performance using the entropy function. The multi‐objective model is compared with modules according to weighted cost function and testing effort measures in a typical modular testing environment.

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Entropy based region reducing genetic algorithm for reliability redundancy allocation in interval environment

Cited by 42 publications

References 24 publications

Redundancy Optimization of an Uncertain Parallel‐Series System with Warm Standby Elements

Redundancy Optimization of an Uncertain Parallel‐Series System with Warm Standby Elements

The Robust Cold Standby Redundancy Allocation in Series-Parallel Systems With Budgeted Uncertainty

Entropy based enhanced particle swarm optimization on multi‐objective software reliability modelling for optimal testing resources allocation

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