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HTTP/2 in action
\"HTTP--Hypertext transfer protocol--is the standard for exchanging messages between websites and browsers. And after 20 years, it's gotten a much-needed upgrade. With support for streams, server push, header compression, and prioritization, HTTP/2 delivers vast improvements in speed, security, and efficiency. 'HTTP/2 in action' teaches you everything you need to know to use HTTP/2 effectively. You'll learn how to optimize web performance with new features like frames, multiplexing, and push. You'll also explore real-world examples on advanced topics like flow control and dependencies. With ready-to-implement tips and best practices, this practical guide is sure to get you, and your websites, up to speed\"--Provided by publisher.
Book
Metaheuristics for the transit route network design problem: a review and comparative analysis
This paper critically reviews applications of metaheuristics for solving the Transit Route Network Design Problem (TRNDP). A structured review is offered and prominent metaheuristics for tackling the TRNDP are evaluated, according to a benchmark network. The review findings yield a unified implementation framework, which contains common algorithmic components and different solution representations and methods, which are considered important for obtaining solutions of good quality. The paper concludes with identified gaps in research and opportunities for future research on the application of metaheuristic algorithms for solving the TRNDP.
Journal Article
The Continuous-Time Service Network Design Problem
Consolidation carriers transport shipments that are small relative to trailer capacity. To be cost effective, the carrier must consolidate shipments, which requires coordinating their paths in both space and time; i.e., the carrier must solve a
service network design
problem. Most service network design models rely on discretization of time—i.e., instead of determining the exact time at which a dispatch should occur, the model determines a time interval during which a dispatch should occur. While the use of time discretization is widespread in service network design models, a fundamental question related to its use has never been answered:
Is it possible to produce an optimal continuous-time solution without explicitly modeling each point in time
? We answer this question in the affirmative. We develop an iterative refinement algorithm using partially time-expanded networks that solves continuous-time service network design problems. An extensive computational study demonstrates that the algorithm not only is of theoretical interest but also performs well in practice.
Journal Article
A bearing fault diagnosis model based on CNN with wide convolution kernels
Intelligent fault diagnosis of bearings is an essential issue in the field of health management and the prediction of rotating machinery systems. The traditional bearing intelligent diagnosis algorithms based on the combination of feature extraction and classification for signal processing require high expert experience, which are time-consuming and lack universality. Compared with traditional methods, the convolutional neural network(CNN) can extract features automatically from the original vibration time-domain signal without any preprocessing. The accuracy of intelligent fault diagnosis can be improved by utilizing the multi-layer nonlinear mapping capability of deep convolutional neural networks. In order to realize the intelligent diagnosis and improve the recognition rate, this paper adopts the strategy of widening convolution kernels to obtain a larger receptive field and proposes a network design process pattern based on this idea, in addition, obtains the convolutional neural network with wide convolution kernels (WKCNN) model through experiments. Based on the time-domain vibration signal, this paper generates more input data through expansion and adopts the wide kernels of the first two convolutional layers to quickly extract features to improve efficiency. The smaller convolution kernels are used for multi-layer nonlinear mapping to deepen the network and improve detection accuracy. The results show that WKCNN performs well in accuracy, anti-noise, and timeliness compared with other diagnostic methods.
Journal Article
Bi-objective emergency blood supply chain network design in earthquake considering earthquake magnitude: a comprehensive study with real world application
This research proposes a new multi-objective mathematical model to design efficient and effective blood supply chain network in earthquakes. For the first time in this field of knowledge, the devastating impact of earthquake destruction radius is considered on blood supply chain network based on its magnitude. Two different transportation means, with variant speed and capacity, are employed to carry the blood from blood collection centers to blood centers. However, the number of available conveyors is limited in each site. To solve the proposed multi-objective mixed integer linear programming model, five multi-objective decision making methods as well as the lexicographic weighted Tchebycheff method are utilized to provide the decision maker with Pareto optimal solutions. Further, the application of the proposed multi-objective mathematical model is investigated in a real-world case study using data from the latest earthquakes in one of the recent activated faults of Iran’s capital, Tehran, which is considered to be a potential place for a severe earthquake. Using different solution approaches, various Pareto optimal solutions are obtained for the case study. The results indicated that the proposed mathematical model is able to design the most cost and time efficient blood supply chain in a severe earthquake. At the end, sensitivity analyses are performed to explore the effects of any changes in main parameters of the multi-objective mathematical model on the objective functions value to demonstrate the most critical parameter.
Journal Article
A survey on the transit network design and frequency setting problem
Appropriate public transport systems are crucial in modern cities. Given the high costs that they represent and the impact they have on people’s lives, effective tools are required to support their design. With this in mind, the Transit Network Design problem (TNDP) and the Transit Network Design and Frequency Setting problem (TNDFSP) have been extensively studied in the domain of Operations Research. However, due to the complexity of these problems, multiple simplifications are typically made when modelling and designing solution algorithms. Therefore, still no optimization techniques are available to address these problems in practice. Moreover, different studies address different versions of the problem, with varying assumptions and constraints, complicating the comparison of results or solution approaches. This paper presents an extensive survey of studies addressing the TNDP and the TNDFSP. It discusses the different assumptions, constraints, objectives, solution approaches and testing instances that have been considered in the literature. Furthermore, a detailed analysis is done regarding the case studies considered for the TNDFSP. Moreover, the variants of the passenger assignment subproblem that have been applied within the TNDP and the TNDFSP are discussed. The analysis shows that extensive research has been done regarding these problems. However, it also identified the significant gap that still exists between theory and practice, even in the studies addressing case studies.
Journal Article
Viable healthcare supply chain network design for a pandemic
The recent COVID-19 pandemic revealed that healthcare networks must have a flexible and effective structure. In this study, we develop a viable healthcare network design for a pandemic using a multi-stage stochastic approach. We propose a multi-level network that includes health centers, computed tomography scan centers, hospitals, and clinics. Patients have conditions to returning to normal life or quarantining at home. Three objectives are defined: maximizing the probability of patient recovery, minimizing the costs of all centers in the network, and minimizing the Coronavirus death rate. We investigate a real case study in Iran to demonstrate the model’s applicability. Finally, we compare the healthcare supply chain network design in a pandemic with a normal situation to advise how the network can continue to remain viable.
Journal Article