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Highlights • A Quick Inclusion-Exclusion (QIE) technique is proposed. • The proposed QIE is for multi-state flow network reliability problems. • The proposed QIE is easy to code and only needs one comparision in each (intersection) term. • The proposed QIE is simpler than the traditional IE. • The proposed QIE is faster than the RSDP which is the most popular sum-of-disjoint product method. Abstract The reliability of modern information systems modeled as multi-state flow networks (MFNs) is a crucial concern the planning, design and control of these systems. The inclusion-exclusion technique (IET) is a popular tool for assessing MFN reliability because it is simple and easily understood. However, it is less efficient than other methods, like the sum-of-disjoint product method (SDP), for example. This paper proposes a new IET, called the Quick Inclusion-Exclusion technique (QIE) to increase the efficiency of the IET and reduce the amount of memory required in MFNs. The correctness and the time complexity of QIE is analyzed and proven. An MFN reliability example is implemented to illustrate the proposed QIE. In order to demonstrate its performance, the proposed QIE is compared with the most popular SDP, the recursive SDP (RSDP) in 20 benchmark networks taken from the literature. Numerical examples demonstrate that the proposed QIE outperforms RSDP in terms of both efficiency and memory use. This result differs significantly from those obtained by traditional methods. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we introduce a novel class of facility location problems, and propose solutions based on Voronoi diagrams. Our solutions locate a set of facilities on a two dimensional space, with respect to a set of dynamic demand. The information about these demand is gathered through modifications of the overall system, into a central decision unit. This influences our objective of minimizing the total loss function. Considering a continuous space and discrete time, facilities are assigned to meet demands in each time cycle. Two distinct approaches are proposed and thoroughly studied, followed by a case study. We call our main algorithm Reactive Agent Dynamic Voronoi Diagram Facility Spread. We also test our solutions empirically through a set of experiments. Considering n and p to be the number of demand points, and the number of facilities in hand, respectively, the time complexity of the algorithm is for a complete run of c cycles. [Copyright &y& Elsevier]

Abstract: This paper describes a new algorithm for the generation of pseudo random numbers with approximate self-similar structure. The Simple Self-Similar Sequences Generator (4SG) elaborates on an intuitive approach to obtain a fast and accurate procedure, capable of reproducing series of points exhibiting the property of persistence and anti-persistence. 4SG has a computational complexity of and memory requirements of the order of , where is the number of points to be generated. The accuracy of the algorithm is evaluated by means of computer-based simulations, recurring to several Hurst parameter estimators, namely Variance Time (VT) and the Wavelets-based estimator. The Hosking and the Wavelets-based methods for the generation of self-similar series were submitted to the same tests the 4SG was analysed with, providing for a basis for comparison of several performance aspects of the algorithm. Results show that the proposal embodies a good candidate not only for on-demand emulation of arbitrarily long self-similar sequences, but also for fast and efficient online simulations. [Copyright &y& Elsevier]