Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Its excellent organizational structure allows quick reference to specific models and its clear presentation. The key findings from the results include the following: (1) the dwell pattern of the taxi fleet determines the siting of charging stations (2) by providing waiting spots, in addition to charging spots, the utilization of chargers increases and the number of required chargers at each site decreases and (3) the tradeoff between installing more chargers versus providing more waiting spaces can be quantified by the cost ratio of chargers and parking spots.read more read lessĪbstract: Praise for the Third Edition: "This is one of the best books available. The proposed method is applied using large-scale GPS trajectory data collected from the taxi fleet of Changsha, China. By means of regression and logarithmic transformation, the charger allocation problem is formulated as an integer linear program (ILP), which can be solved efficiently using Gurobi solver. To account for charging congestion, an M / M / x / s queueing model is adopted to estimate the probability of BEV taxis being charged at their dwell places. Abstract: This paper presents a data-driven optimization-based approach to allocate chargers for battery electric vehicle (BEV) taxis throughout a city with the objective of minimizing the infrastructure investment.
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