Skip to content
Research Article Open access CC BY 4.0

Conventional and Improved Inclusion-Exclusion Derivations of Symbolic Expressions for the Reliability of a Multi-State Network

Ali Muhammad Ali Rushdi, Motaz Hussain Amashah

Asian Journal of Research in Computer Science · pp. 21–45 · Published 27 Apr 2021

10.9734/ajrcos/2021/v8i130191

Abstract

This paper deals with an emergent variant of the classical problem of computing the probability of the union of n events, or equivalently the expectation of the disjunction (ORing) of n indicator variables for these events, i.e., the probability of this disjunction being equal to one. The variant considered herein deals with multi-valued variables, in which the required probability stands for the reliability of a multi-state delivery network (MSDN), whose binary system success is a two-valued function expressed in terms of multi-valued component successes. The paper discusses a simple method for handling the afore-mentioned problem in terms of a standard example MSDN, whose success is known in minimal form as the disjunction of prime implicants or minimal paths of the pertinent network. This method utilizes the multi-state inclusion-exclusion (MS-IE) principle associated with a multi-state generalization of the idempotency property of the ANDing operation. The method discussed is illustrated with a detailed symbolic example of a real-case study, and it produces a more precise version of the same numerical value that was obtained earlier. The example demonstrates the notorious shortcomings and the extreme inefficiency that the MS-IE method suffers, but, on the positive side, it reveals the way to alternative methods, in which such a shortcoming is (partially) mitigated. A prominent and well known example of these methods is the construction of a multi-state probability-ready expression (MS-PRE). Another candidate method would be to apply the MS-IE principle to the union of fewer (factored or composite) paths that is converted (at minimal cost) to PRE form. A third candidate method, employed herein, is a novel method for combining the MS-PRE and MS-IE concepts together. It confines the use of MS-PRE to ‘shellable’ disjointing of ORed terms, and then applies MS-IE to the resulting partially orthogonalized disjunctive form. This new method makes the most of both MS-PRE and MS-IE, and bypasses the troubles caused by either of them. The method is illustrated successfully in terms of the same real-case problem used with the conventional MS-IE.

Network reliability inclusion-exclusion probability-ready expression multi-state system symbolic expression multi-state delivery network

Cited by 10

Assessment of reliability and maintenance models with time parameters in stochastic flow networks

Ping-Chen Chang, Lance Fiondella, Ding-Hsiang Huang · Engineering optimization (Print) · 2025

A reliability prediction model for a multistate cloud/edge-based network based on a deep neural network

Ding-Hsiang Huang, Cheng-Fu Huang, Yi-Kuei Lin · Annals of Operations Research · 2022

Network reliability evaluation of manufacturing systems by using a deep learning approach

Cheng-Fu Huang, Ding-Hsiang Huang, Yi-Kuei Lin · Annals of Operations Research · 2022

System Reliability of a Modern Distributed Network with Node Failure and Budget Consideration Using Analytical Algorithm and Deep Learning Model

Ding-Hsiang Huang, Ping-Chen Chang · International Journal of Reliability, Quality and Safety Engineering · 2024

Article metrics

Real usage data collected on this platform.

0

Page views

0

PDF downloads

0

Outbound clicks

10

Citations

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

No views recorded yet.

Traffic sources

Referring site, by host.

No traffic recorded yet.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.