With the explosive growth of wireless data transmission, wireless content sharing is facing significant challenges such as a surge in data transmission scale, resource shortages, and a volatile communication environment. Consequently, dynamic caching technology based on D2D communication has emerged. Cache network is a distributed network architecture where network nodes (such as user devices or base stations) have caching capabilities and can store part of the content to reduce content transmission delay and network traffic. In cache networks, considering the short distance characteristics of direct device communication and the self offloading advantage of user caching, a cache mechanism is proposed. The paper analyzes the file offload capability and packet loss rate of the cache network. First, this paper analyzes network interference. Considering the randomness of content caching and requests, it derives a closed-form expression of the successful transmission probability based on random geometric theory. Secondly, considering the randomness of content requests and the limited cache capacity, a user cache queue model is established to analyze the transmission process of request files, and an M/G/1 queuing service model is established. The files requested by users can be obtained through two offloading methods: self offloading and device direct connection (D2D) communication offloading. The queue state of the files is constructed as a Markov chain, and the file queue state under different transmission modes is analyzed. Key performance parameter expressions such as successful offloading probability are obtained. Simulation shows that in networks with D2D assisted caching, in the actual situation of limited cache space, the higher the popularity index, the easier it is for the requested content to be satisfied by its own cache, the smaller the cache queue length, and the lower the packet loss rate. Auxiliary caching strategies can leverage the advantages of their own caching and D2D communication, effectively reducing the mean delay for users to obtain request files.

Tehran, as one of the most populated capital cities worldwide, is categorized in the group of highly polluted cities in terms of the geographical location as well as increased number of industries, vehicles, domestic fuel consumption, intra-city trips, increased manufacturing units, and in general excessive increase in the consumption of fossil energies. City logistics models can be effectively helpful for solving the complicated problems of this city. In the present study, a queuing theory-based bi-objective mathematical model is presented, which aims to optimize the environmental and economic costs in city logistics operations. It also tries to reduce the response time in the network. The first objective is associated with all beneficiaries and the second one is applicable for perishable and necessary goods. The proposed model makes decisions on urban distribution centers location problem. Subsequently, as a case study, the fruit and vegetable distribution network of Tehran city is investigated and redesigned via the proposed modelling. The results of the implementation of the model through traditional and augmented ε-constraint methods indicate the efficiency of the proposed model in redesigning the given network.

Today, urban areas have been considerably expanded, which has caused numerous problems due to the large population in metropolitan areas. City logistics models can be effective in solving complicated problems such as traffic congestion, air pollution, accidents, and high energy consumption rate. The present paper proposes a bi-objective mathematical model for designing a city logistics distribution network in order to minimize the economic and environmental costs as well as the response time. The proposed model would make decisions on the location and allocation problems in the city logistics distribution network. In fact, the objective of the problem is to select some fixed sites in order to construct the city distribution centers. The demand for commodities is considered probabilistic and the network is modeled based on the queuing theory. Furthermore, in the proposed model, the policy of putting tax on carbon and applying the low-carbon emission resources are used for establishment at the city distribution centers. Afterwards, in order to validate the proposed model, a numerical example is generated and, then, the results obtained from solving the model via epsilon constraint method are presented. Analysis of the results in the present study indicates that the proposed model was highly efficient in achieving its objectives. Finally, there are some suggestions for future studies that can be taken into account.

The improvement in the provision of banking services to customers enhances bank’s performance (profitability and productivity) and the amounts of dividend declared to shareholders as well as bank’s competitiveness. One means of fast tracking the service time for bank customers is through the use of self-servicing machines, such as automated teller machine (ATM). Total service cost, expected waiting time in queue, ATM utilization and percentage of customer loss are some of the performance indices that are used to evaluate the service rendered by a bank’s ATM. This study proposes a framework for evaluating the performance of ATM by integrating queuing model and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodology. Applicability of the framework was tested using practical data obtained from four banks in Nigeria. It was observed that the average ATM usage in the study area was less than 50%. The TOPSIS results identified Bank A as the best ranked bank. In addition, the results obtained revealed that banks with two ATM were ranked higher than banks with more than two ATM.