Evaluating the system reliability of a stochastic network is an important topic in the planning, designing and control of systems. It is always desirable to minimise the resource consumption, e.g., the total cost, under the network reliability constraint in a real-life network problem. In this study, an intuitive Monte Carlo simulation (MCS) was first developed to find the estimated reliability w.r.t some specific combinations of the node reliability. Then, the response surface methodology (RSM) with the Box-Behnken design (BBD) was implemented to obtain the reliability function. Next, the proposed problem was modelled and solved by nonlinear programming. One example is given to illustrate the proposed MCS-RSM approach
Abstract:- In this paper we focus on computational aspects of network reliability importance measure...
This article presents Monte Carlo techniques for estimating network reliability. For highly reliable...
In this paper we consider the evaluation of a well Known K-network unreliability parameter by means ...
Designing a network with optimal deployment cost and maximum reliability considerations is a hard pr...
Network reliability is very important for the decision support information. Monte Carlo Simulation (...
[[abstract]]Simulations have been applied extensively to solve complex problems in real-world. They ...
Abstract:- The reliability at required demand level d (M2Rd) is usually selected as the most importa...
The exact evaluation of usual reliability measures of communication networks is seriously limited be...
This paper provides a detailed review of the state of the art in the field of network reliability an...
[[abstract]]To evaluate the multi-state network reliability at required demand level d(M2Rd) is a NP...
This paper presents a methodology for general nonlinear reliability problems. It is based on dividin...
[[abstract]]The reliability at required demand level d (M2Rd) is usually selected as the most import...
This paper presents a reliability-based network design problem. A network reliability concept is emb...
The stochastic response surface method (SRSM) and the response surface method (RSM) are often used f...
Reliability optimization has been a popular area of research, and received significant attention due...
Abstract:- In this paper we focus on computational aspects of network reliability importance measure...
This article presents Monte Carlo techniques for estimating network reliability. For highly reliable...
In this paper we consider the evaluation of a well Known K-network unreliability parameter by means ...
Designing a network with optimal deployment cost and maximum reliability considerations is a hard pr...
Network reliability is very important for the decision support information. Monte Carlo Simulation (...
[[abstract]]Simulations have been applied extensively to solve complex problems in real-world. They ...
Abstract:- The reliability at required demand level d (M2Rd) is usually selected as the most importa...
The exact evaluation of usual reliability measures of communication networks is seriously limited be...
This paper provides a detailed review of the state of the art in the field of network reliability an...
[[abstract]]To evaluate the multi-state network reliability at required demand level d(M2Rd) is a NP...
This paper presents a methodology for general nonlinear reliability problems. It is based on dividin...
[[abstract]]The reliability at required demand level d (M2Rd) is usually selected as the most import...
This paper presents a reliability-based network design problem. A network reliability concept is emb...
The stochastic response surface method (SRSM) and the response surface method (RSM) are often used f...
Reliability optimization has been a popular area of research, and received significant attention due...
Abstract:- In this paper we focus on computational aspects of network reliability importance measure...
This article presents Monte Carlo techniques for estimating network reliability. For highly reliable...
In this paper we consider the evaluation of a well Known K-network unreliability parameter by means ...