In this chapter, you will see how the simplex method simplifies when it is applied to a class of optimization problems that are known as “network flow models.” You will also see that if a network flow model has “integer-valued data,” the simplex method finds an optimal solution that is integer-valued.

Flows in Networks

A review of reverse logistics and closed-loop supply chains: a Journal of Cleaner Production focus

(2007). Stochastic Ageing and Dependence for Reliability. Technometrics: Vol. 49, No. 2, pp. 222-222.

Stochastic Ageing and Dependence for Reliability

Reliability engineering dates back to reliability studies in the 20th century; since then, various models have been defined and used. Software engineering plays a key role from several viewpoints, but the main concern is that we're moving toward a more connected world, including enterprises and mobile devices. The three articles in this special issue illustrate current trends in this domain.

Reliability Engineering

We present a descriptive literature review and classification scheme for cloud computing research. This includes 205 refereed journal articles published since the inception of cloud computing research. The articles are classified based on a scheme that consists of four main categories: technological issues, business issues, domains and applications, and conceptualising cloud computing. The results show that although current research is still skewed towards technological issues, new research themes regarding social and organisational implications are emerging. This review provides a reference source and classification scheme for IS researchers interested in cloud computing, and to indicate under-researched areas as well as future directions.

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A Descriptive Literature Review and Classification of Cloud Computing Research

From the perspective of network analysis, the manufacturing system can be constructed as a stochastic-flow network, since the capacity of each machine is stochastic (i.e. multistate) owing to the failure, partial failure, and maintenance. Considering reworking action and different failure rates of machines, the input flow (raw materials/work in process) processed by each machine might be defective, and therefore the output flow (work in process/products) would be less than the input amount. To evaluate the capability of the manufacturing system, we measure the probability that the manufacturing network can satisfy demand. Such a probability is defined as the system reliability. A decomposition method is first proposed to divide the manufacturing network into one general processing path and one reworking path. Subsequently, two algorithms are utilised for different network models to generate the lower boundary vector of machine capacity to guarantee that the manufacturing network is able to produce suffici...

System reliability of a manufacturing network with reworking action and different failure rates

The cloud computing network (CCN) has become a new paradigm for the business and clients as the development of information technology. To guarantee the CCN keep a good quality of service (QoS), the maintenance action is necessary when the CCN falls to a specific state such that it cannot afford enough capacity to meet demand d. In the CCN, edges and nodes have various capacities due to failure, partial failure, or maintenance; thus, the CCN has several possible states. This paper proposes an algorithm to estimate the performance of a CCN under maintenance budget with nodes failure. Hence, the maintenance reliability is developed to measure the capability that the CCN can send d units of data from the cloud to the client through multiple paths under the maintenance budget and time constraints. Furthermore, the system supervisor can conduct the sensitive analysis to improve/investigate the most important part in a large CCN afterwards.

Maintenance reliability estimation for a cloud computing network with nodes failure

Evaluate the system reliability for a manufacturing network with reworking actions

This paper presents a novel technique to measure the performance of a stochastic-flow manufacturing network (SMN) which violates the so-called flow conservation law due to the failure rates of stations. We address the mission reliability, the probability of demand satisfaction, as a performance indicator for the SMN while considering both the stochastic capacities and the multiple production lines. First, we construct a manufacturing system as an SMN through a graphical transformation, and decompose the transformed SMN into several paths for further analysis. Subsequently, two algorithms for different scenarios are designed to generate all minimal capacity vectors that stations should provide to satisfy the given demand. The first scenario is for the SMN with identical production lines in parallel. The second scenario is for distinct production lines with common stations in the SMN. We derive the mission reliability in terms of minimal capacity vectors by applying the recursive sum of disjoint products (RSDP) algorithm. A decision making issue is also discussed to decide a reliable production strategy.

Ping Chen Chang

Papers

System reliability of a manufacturing network with reworking action and different failure rates

Maintenance reliability estimation for a cloud computing network with nodes failure

Evaluate the system reliability for a manufacturing network with reworking actions

A Novel Reliability Evaluation Technique for Stochastic-Flow Manufacturing Networks With Multiple Production Lines

System reliability estimation and sensitivity analysis for multi-state manufacturing network with joint buffers––A simulation approach