Search Results (7)

The development of the new energy vehicle (NEV) market in China has promoted the sustainability of the automotive industry, but has also brought pressures to NEV charging infrastructure. This paper aims to determine the strategic role of charging stations, particularly on whether they should provide service for plug-in hybrid electric vehicles (PHEVs) in the highway service area during peak holidays. Firstly, the charging service resource allocation for a charging station that provides services for both electronic vehicles (EVs) and PHEVs is studied. Secondly, different queueing disciplines are compared. At last, a comparison between scenarios where charging services are limited to EVs and those where services extend to both EVs and PHEVs is conducted. A queueing system considering customer balking and reneging is developed. The impacts of parameters, such as the NEV arrival rate and patience degree of different NEV drivers, on the optimal allocation plan, profit, and comparison results are discussed. The main conclusions are as follows: (1) If the EV arrival rate is greater than the charging service rate, the charging station should not provide charging services for PHEVs. Providing service only for EVs derives more revenues and profits and results in a shorter waiting queue. Conversely, if the total arrival rate of NEVs (including EVs and PHEVs) is lower than the charging service rate, then the charging station should also serve PHEVs. (2) If providing service for PHEVs, a mixed queueing discipline should be applied when the total arrival rate approximates the service rate. When the total NEV arrival rate is significantly lower than the charging service rate, the separate queueing discipline should be adopted. (3) When applying a separate queueing discipline, if a certain type of NEV has a higher arrival rate and the drivers exhibit greater patience, then more charging resources should be allocated to this type of NEV. If the charging service is less busy, the more patient the drivers are, the less service resources should be allocated to them, whereas, during peak times, the more patient the drivers are, the more service resources should be allocated to them. Full article

In this article, we consider a make-to-stock queueing system with retrial customers. Upon their arrival, customers make a decision to either join the system or not based on a reward–cost function. If customers join the retrial queue, they become repeat customers. Each repeat customer repeats their demand after an exponential amount of time until they have been successfully served. We explore the equilibrium strategies of customers in both the almost observable and unobservable cases. Furthermore, we also analyze the expected costs of the entire system based on the customers’ behavior in these two cases. Additionally, we determine the optimal inventory levels in both cases through numerical experiments. Full article

Various transportation services exist, such as ride-sharing or shared taxis, in which customers receive services in a batch of flexible sizes and share fees. In this study, we conducted an equilibrium analysis of a variable batch service model in which customers who observe no waiting customers in an incomplete batch can strategically select a batch size to maximize the individual utilities. We formulated this model as a three-dimensional Markov chain and created a book-type transition diagram. To consider the joining/balking dilemma of customers for this model, we proposed an effective algorithm to construct a necessary and sufficient size of state space for the Markov chain provided that all customers adopt the threshold-type equilibrium strategy. Moreover, we proved that the best batch size is a non-decreasing function for i if the reward for the completion of batch service with size l is an increasing function of l assuming that a tagged customer observes i complete batches in the system upon arrival; in other words, the fee decreases as the batch becomes larger. We then derive several performance measures, such as throughput, social welfare, and monopolist’s revenue. Throughout the numerical experiment, a comparison between the present variable batch service model and regular batch service model in which customers were served in a constant batch, was discussed. It was demonstrated that the three performance measures can be optimized simultaneously in the variable batch service model, as long as the fee was set relatively high. Full article

We find an equilibrium in a single-server queueing system with retrials and strategic timing of the customers. We consider a set of customers, each of which must decide when to arrive to a queueing system during a fixed period of time. In this system, after completion of service, the server seeks a customer blocked in a virtual orbit (orbital customer) to be served next, unless a new customer captures the server. We develop, in detail, a setting with two and three customers in the set, and formulate and discuss the problem for the general case with an arbitrary number of customers. The numerical examples for the system with two and three customers included as well. Full article

This article studies the strategic access of single-server retrial queue with two types of customers, where priority is given according to their category. On the basis of this concept, a cognitive-radio network was developed as retrial queue with energy harvesting. Cognitive radio allows for a secondary user to opportunistically access the idle spectrum of a primary user (PU). Upon arrival of a primary user, the service given to the secondary user by the cognitive radio is interrupted, and the PU band is available for the primary user. After completion of service for the primary user, the PU band is again available to secondary users. Performance metrics are derived to study the equilibrium strategies of secondary users. A Stackelberg game was formulated and Nash equilibrium was derived for the noncooperative strategy of the secondary user. Game-theory concepts are incorporated with queuing theory ideas to obtain the net benefit for the noncooperative strategy and social benefit for cooperative strategy. Lastly, analytical results are verified with numerical examples, and the effects of energy-harvesting rate are discussed. Full article

We study strategic behavior in the $Geo/Ge{o}^K/1$ queueing system under both fully observable case and fully unobservable case. Furthermore, equilibrium and socially optimal strategies are obtained according to the available information and the linear utility function. We compare the impact of system parameters on the equilibrium strategies and socially optimal strategies. At the same time, we illustrate the effects of parameters on the obtained equilibrium social benefit. Finally, some numerical examples are presented. Full article

We consider a three-tiered cloud service market and propose an energy efficient pricing strategy in this market. Here, the end customers are served by the Software-as-a-Service (SaaS) providers, who implement customized services for their customers. To host these services, these SaaS providers, in turn, lease the infrastructure related resources from the Infrastructure-as-a-Service (IaaS) or Platform-as-a-Service (PaaS) providers. In this paper, we propose and evaluate a mechanism for pricing between SaaS providers and Iaas/PaaS providers and between SaaS providers and the end customers. The pricing scheme is designed in a way such that the integration of renewable energy is promoted, which is a very crucial aspect of energy efficiency. Thereafter, we propose a technique to strategically provide an improved Quality of Service (QoS) by deploying more resources than what is computed by the optimization procedure. This technique is based on the square root staffing law in queueing theory. We carry out numerical evaluations with real data traces on electricity price, renewable energy generation, workload, etc., in order to emulate the real dynamics of the cloud service market. We demonstrate that, under practical assumptions, the proposed technique can generate more profit for the service providers operating in the cloud service market. Full article