Browsing by Author "Huang, Ding-Hsiang"

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A Binding Algorithm of Lower Boundary Points Generation for Network Reliability Evaluation
(2020-09-01)
Huang, Ding-Hsiang
;
Huang, Cheng-Fu
;
Lin, Yi-Kuei
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Network reliability evaluation for a stochastic flow network (SFN) can be computed in terms of all lower boundary points (LBPs). Although several algorithms have been presented in the literature as solutions for the LBP problem, the efficiency is always occurring at the present for the large SFN. In this paper, a binding technique generating binding-flow vectors is therefore developed to narrow down the searching range of flows for demand. This technique is able to reduce the loading of the candidate comparison procedure greatly. An algorithm based on this binding technique is proposed to solve the LBP problem. We compare the performance of the proposed algorithm to well-known algorithms in terms of CPU time, through three benchmark networks and a practical case. The experimental results show the functional efficiency of our proposed binding LBP algorithm.
A novel minimal cut-based algorithm to find all minimal capacity vectors for multi-state flow networks
(2020-05-01)
Huang, Ding-Hsiang
;
Huang, Cheng-Fu
;
Lin, Yi-Kuei
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
y Real systems, such as computer systems, can be modeled as network topologies with vertices and edges. Owing to equipment failures and maintenance requirements, the capacities of edges have several states. Such systems are regarded as multi-state flow networks (MSFN). System reliability of an MSFN is the probability that the required flow (i.e., demand) can successfully be sent from the source to the sink. By adopting a minimal path (MP) approach, system reliability can be computed in terms of all minimal capacity vectors meeting the demand d. A minimal capacity vector is called a d-MP. Although several algorithms have been presented in the literature for finding all d-MP, improving efficiency in the search for all d-MP is always a challenge. A group approach with both the concepts of minimal cut and MP is developed in this study, narrowing the search range of feasible flow vectors. An algorithm based on the group approach is then proposed to improve the efficiency of the d-MP search. According to the structure of the proposed algorithm, parallel computing can be implemented with significant improvement in the efficiency of the d-MP generation, where the proposed algorithm is compared with previous ones based on three benchmarks, in terms of CPU time. (C) 2019 Elsevier B.V. All rights reserved.
Exact project reliability for a multi-state project network subject to time and budget constraints
(2020-03-01)
Huang, Ding-Hsiang
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Huang, Cheng-Fu
;
Lin, Yi-Kuei
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
In a project, the duration of every activity is uncertain because of weather, availability of machines, human resources, and unexpected situations, and the cost is influenced by the duration. For modeling the uncertain durations, a multi-state project network (MPN) is proposed. To understand the performance of an MPN, project reliability is calculated and defined as the probability that a project can be completed within time and budget constraints. All feasible project state vectors are contained in upper and lower boundary points. The previous literature only calculated an estimated project reliability. To obtain the exact project reliability, a decomposition approach is developed to obtain subsets of feasible project state vectors. Each subset is firstly formed in terms of one upper boundary point and all lower boundary points. Each subset is further simplified to reduce the number of lower boundary points for computational efficiency. An algorithm with the decomposition approach is subsequently proposed to evaluate the exact project reliability. A real project of new manufacturing lines is demonstrated with several combinations of time and budget constraints to show the effectiveness of the proposed algorithm, and project managers can make decisions based on project reliability.
Network reliability evaluation for a distributed network with edge computing
(2020-09-01)
Huang, Cheng-Fu
;
Huang, Ding-Hsiang
;
Lin, Yi-Kuei
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Reliability and speed are crucial for ensuring robustness in a computer network, which is used for sharing information and resources within a business. The two most recent and important developments in the field of computing are cloud computing and edge computing. In this study, a modern distributed network comprising computers, internet of things (IoT), edge servers, and cloud servers for data transmission was investigated. A distributed network can be modeled as a graph with nodes and arcs, in which each arc represents a transmission line, and each node represents an IoT device, an edge server, or a cloud server. The data are transmitted through these transmission lines which are combined with numerous physical lines such as fiber cables. Therefore, each transmission line has several possible capacities and the capacity of each arc in the distributed network can be regarded as a multistate. Such the distributed network is called a multi-state distributed network (MDN). In an MDN, the data produced by IoT devices are transmitted to the edge servers. After being processed and compressed by the edge servers, the data are then transmitted to the cloud servers for advance computing. The purpose of this study is to first construct a model of a network in order to elucidate the flow relationship among the IoT devices, edge servers, and cloud servers and subsequently develop an algorithm to evaluate network reliability, which is the probability of the data being successfully processed by the MDN.
Reliability Evaluation for a Stochastic Flow Network Based on Upper and Lower Boundary Vectors
(2019-11-01)
Huang, Ding-Hsiang
;
Huang, Cheng-Fu
;
Lin, Yi-Kuei
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
For stochastic flow network (SFN), given all the lower (or upper) boundary points, the classic problem is to calculate the probability that the capacity vectors are greater than or equal to the lower boundary points (less than or equal to the upper boundary points). However, in some practical cases, SFN reliability would be evaluated between the lower and upper boundary points at the same time. The evaluation of SFN reliability with upper and lower boundary points at the same time is the focus of this paper. Because of intricate relationships among upper and lower boundary points, a decomposition approach is developed to obtain several simplified subsets. SFN reliability is calculated according to these subsets by means of the inclusion-exclusion principle. Two heuristic options are then established in order to calculate SFN reliability in an efficient direction based on the lower and upper boundary points.