Jesús R. Artalejo

Bio: Jesús R. Artalejo is an academic researcher from Complutense University of Madrid. The author has contributed to research in topics: Retrial queue & M/G/1 queue. The author has an hindex of 33, co-authored 102 publications receiving 4637 citations. Previous affiliations of Jesús R. Artalejo include Kettering University.

Retrial Queueing Systems: A Computational Approach

Abstract: The application of auto-repeat facilities in telephone systems, as well as the use of random access protocols in computer networks, have led to growing interest in retrial queueing models. Since much of the theory of retrial queues is complex from an analytical viewpoint, with this book the authors give a comprehensive and updated text focusing on approximate techniques and algorithmic methods for solving the analytically intractable models. Retrial Queueing Systems: A Computational Approach also * Presents motivating examples in telephone and computer networks. * Establishes a comparative analysis of the retrial queues versus standard queues with waiting lines and queues with losses. * Integrates a wide range of techniques applied to the main M/G/1 and M/M/c retrial queues, and variants with general retrial times, finite population and the discrete-time case. * Surveys basic results of the matrix-analytic formalism and emphasizes the related tools employed in retrial queues. * Discusses a few selected retrial queues with QBD, GI/M/1 and M/G/1 structures. * Features an abundance of numerical examples, and updates the existing literature. The book is intended for an audience ranging from advanced undergraduates to researchers interested not only in queueing theory, but also in applied probability, stochastic models of the operations research, and engineering. The prerequisite is a graduate course in stochastic processes, and a positive attitude to the algorithmic probability.

A First Course in Stochastic Models

Abstract: Poission process and related processes renewal-reward processes discrete-time Markov chains continuous-time Markov chains Markov chains and queues discrete-time Markov decision processes semi-Markov decision processes advanced renewal theory algorithms analysis of queuing models useful tools in applied probability useful probability distributions generating functions the discrete fast Fourier transform Laplace transformtheory numerical Laplace inversion the root-finding problem.

Optimization models in emergency logistics: A literature review

Abstract: Optimization modeling has become a powerful tool to tackle emergency logistics problems since its first adoption in maritime disaster situations in the 1970s. Using techniques of content analysis, this paper reviews optimization models utilized in emergency logistics. Disaster operations can be performed before or after disaster occurrence. Short-notice evacuation, facility location, and stock pre-positioning are drafted as the main pre-disaster operations, while relief distribution and casualty transportation are categorized as post-disaster operations. According to these operations, works in the literature are broken down into three parts: facility location, relief distribution and casualty transportation, and other operations. For the first two parts, the literature is structured and analyzed based on the model types, decisions, objectives, and constraints. Finally, through the content analysis framework, several research gaps are identified and future research directions are proposed.