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Reasonable earthmoving-equipment combinations have helped to reduce duration and cost in the construction industry traditionally. However, reducing carbon emissions in earthmoving operations is highly desirable because earthmoving operations involve a large number of heavy equipment, which produce high carbon emissions. It is necessary to study a novel equipment combination optimization model considering decreasing carbon emissions in addition to duration and cost. Hence, a triobjective equipment combination optimization (ECO) model is developed, minimizing carbon emissions as well as project duration and cost. In this model, the excavation and transportation processes of earthwork are regarded as a queuing system, and queuing theory is integrated directly into the model to compute the involved parameters instead of a simulation. On the other hand, for obtaining the optimal solution set of the multiobjective problems with more objectives, a novel two-archive multiobjective particle swarm algorithm is proposed, which updates individuals in archives by not only Pareto domination but also an indicator that can assess solution quality. A real case study demonstrated that the model can efficiently provide a reasonable earthmoving-equipment combination considering the trade-off among carbon emissions, duration, and cost for managers. A multiobjective model for obtaining the optimal earthmoving-equipment combination is proposed in this paper. In addition to traditional reductions in duration and cost, the model also considers sustainability requirements by reducing carbon emissions in the construction industry. In other words, this model can offer the solutions of equipment combinations in terms of not only reducing the cost and duration to construction managers, but also reducing carbon emissions. Instead of one combination of earthmoving equipment, a set of nondominated solutions is offered in this model, and this allows managers to make choices based on specific site conditions. In addition, the authors have improved the traditional algorithm to obtain the solutions to better meet the needs of users. This new earthmoving-equipment combination optimization model can quickly get reasonable equipment combinations and helps minimize carbon emissions as well as duration and cost. This model has been applied to a real earthwork project in China and gave the optimal excavator-truck configuration that satisfied the contractor. [ABSTRACT FROM AUTHOR]

Reverse referral implies referring patients from a comprehensive hospital to a community healthcare centre. In recent years, it has become popular for post-acute care in the tiered Chinese hospital system as it helps achieve more balanced utilisation between facilities at different levels. Nevertheless, it remains unclear how to implement the reverse referral partnership given the likely conflicting interests between the involved hospitals. In this paper, we evaluate a reversal referral partnership involving one hospital of each type, for which we develop queuing models for the two hospitals to capture multiple patient waits, services and transitions, with reverse referral in place. We use queuing-based performance outcomes to evaluate the profitability of each hospital and its willingness to join the partnership. We combine the above evaluations to further assess the partnership effectiveness. Through this work, we expect to provide policy insights to the government for forming hospital partnerships effectively. [ABSTRACT FROM PUBLISHER]

In the face of an increasingly high-demand environment for outpatients, achieving a balance between allocation of limited medical resources and patient satisfaction has considerable social and economic benefits. Therefore, appointment scheduling (AS) system operation is used in clinics and hospitals, and its operation optimization research is of great significance. This study reviews the research progress on appointment scheduling system optimization. Firstly, we classify and conclude the existing appointment scheduling system structures and decision-making frameworks. Subsequently, we summarize the system reliability optimization framework from three aspects: appointment scheduling system optimization objectives, decision variables and constraints. Following that, we methodically review the most applied system optimization algorithms in different appointment scheduling systems. Lastly, a literature bibliometric analysis is provided. During our review of the literature, we observe that (1) optimization methods in ASs predominantly involve the application of genetic algorithms and simulation optimization algorithms; (2) neural networks and deep learning methods are core technologies in health management optimization; (3) a bibliometric analysis reveals a heightened interest in the optimization technology of ASs within China compared to other nations; and (4) further advancements are essential in the comprehensive optimization of the system, exploration of practical usage scenarios, and the application of advanced simulation and modeling techniques in this research. [ABSTRACT FROM AUTHOR]

This paper investigates appointment scheduling for an outpatient department in West China Hospital (WCH), one of the largest single point of access hospitals in the world. Our pilot data analysis shows that the appointment system at WCH can be improved through leveraging the scheduling window (i.e., the number of days in advance a patient makes an appointment for future services). To gain full insight into this strategy, our study considers two cases, based on if patients are willing to wait for scheduled appointments or not. We developed a stylized single server queueing model to find optimal scheduling windows. Results show that, when patients are less sensitive to time delay (i.e., patients will wait for scheduled services), levering scheduling windows is not effective to minimize the total cost per day of the appointment system. In contrast, when patients are sensitive to time delay (i.e., patients may find services elsewhere), then our model considers the potential cost of physician idle time. The modeling results indicate that the total cost per day is relatively sensitive to the magnitude of scheduling window. Thus, adopting a proper scheduling window is very important. In addition, our study proves that the cost functions of both cases are quasi-concave, which are also validated by actual data drawn from the Healthcare Information System at WCH. A comparison of numerical results between two cases is made to draw further managerial insights into scheduling policies for WCH. Discussion of our findings and research limitations are also provided. [ABSTRACT FROM AUTHOR]

China Railway Express has been developed rapidly since “the Belt and Road Initiative” in China was proposed. Many cities in the Midwest of China have developed into the transport hub from the transport terminal. The key question is how to reasonably formulate the size of the container station and the frequency of the shift for China Railway Express. This paper takes the container as the research object. Regarding the containers as customers in the queuing system, customers’ services ending with the loading of containers into China Railway Express, based on a finite-capacity queueing system with batch service, this paper provides an optimal layout method for the container yard of China Railway Express. [ABSTRACT FROM AUTHOR]

Presents a queuing theory model which includes the effect of seasonal changes on the performance of the Kwai Chung Container Terminals in Hong Kong, China. Parameters of the queuing theory model; Methods used to estimate average port arrival time of container vessels per month; Analysis of possible model shortcomings; Techniques for managing seasonal fluctuation of container throughput in the terminals.

This paper is intended to give a survey of the main results of queueing theory in China. It consists of five parts: (1) the transient behaviour of typical queueing systems; (2) classical problems; (3) approximation theory; (4) model structure; (5) applications. [ABSTRACT FROM AUTHOR]

Users of escalators and moving walkways with sufficient space to accommodate two lanes of users often follow an implied etiquette for the two lanes: one for walking and one for standing (in the US, China, and many countries, the convention is "walk left, stand right"). When there is high volume, e.g., when exiting a subway or train station or at the conclusion of an athletic event, the escalators often experience bottleneck congestion that constitutes the primary source of delay. It has been suggested that during such high-congestion periods, it would be more efficient if everyone just stood in both lanes, with empirical evidence used to support this counterintuitive finding. Simple deterministic queueing models are used to show under what conditions such results hold and also to provide further insights regarding tradeoffs between performance metrics as a function of the distribution of walkers and standers, which could inform practical implementation policies to increase efficiency. [ABSTRACT FROM AUTHOR]

Due to cope with relying on controllers badly and lacking of quantitative models to assist decision-making in air traffic flow management, this paper studied the delay optimization model and its solving algorithm for route network. Firstly, it established a traffic flow assignment model with the objective function of minimum flight time and capacity constraints. Secondly, considering that classical Hungarian algorithm was only suitable for small and medium-sized operations, it made the improvement of the calculation of efficiency matrix by making the maximum probability of the number of zero elements in the circle equal to the order of the efficiency matrix. Next, it constructed the cost function of the en-route by using the MIMIC queuing theory model. The function, which replaced the constant efficiency value in the efficiency matrix with a variable cost, made the efficiency matrix change with time and flow. Finally,it took part airspaces of China and the actual operational data of 2016 as examples. The results show that the algorithm can increase the access capacity by 8. 372% and the departure capacity by 8. 999%; In terms of delay optimization,it can reduce the average delay of each aircraft. In terms of algorithm performance, it has less iterations and less solution time than the classical Hungarian algorithm, and is more suitable for actual control operation. [ABSTRACT FROM AUTHOR]

In this paper, a multi-objective decision aiding model is introduced for allocation of beds in a hospital. The model is based on queuing theory and goal programming (GP). Queuing theory is used to obtain some essential characteristics of access to various departments (or specialities) within the hospital. Results from the queuing models are used to construct a multi-objective decision aiding model within a GP framework, taking account of targets and objectives related to customer service and profits from the hospital manager and all department heads. The paper describes an application of the model, dealing with a public hospital in China that had serious problems with loss of potential patients in some departments and a waste of hospital beds in others. The performance of the model and implications for hospital management are presented. [ABSTRACT FROM AUTHOR]

With the intensification of aging, more and more elderly people in China live alone and face the dilemma of less and less communication. However, an intrinsic requirement for the elderly to be accompanied and heard increases the demand for emotional care services. Hence, we focus on emotional care for the elderly and propose the multi-agency bi-objective elderly emotional care routing and scheduling model that considers both the travel and overtime costs of caregivers together with customers' preferences for caregivers. We expand a single agency service mode to a multi-agency joint service mode to avoid a decline in customer satisfaction due to the fact that the single agency cannot meet all customers' requirements in time. In addition, we design a merging method of nearby requirement points to save costs, which permits the same caregiver to provide services to customers in close geographic proximity at the same time on the premise that customers are willing to receive emotional care services with others. We add the constraint that every requirement cannot be rejected, ensuring that all requirements will be responded to. The results show that in the multi-agency joint service mode, all requirements are met without rejection. Compared with the single-agency service model, the proposed model can realize higher customer satisfaction at lower cost, which verified that the proposed multi-agency joint service mode can better meet the needs of a large number of elderly persons' emotional care. [ABSTRACT FROM AUTHOR]

This study aimed to calibrate saturation flow rate (SFR) and start-up lost time (SLT) when developing signal timing. In current commonly used methods, SFR for one given lane is usually calibrated from many subjective adjustment factors and a fixed result. SLT is calculated based on the fixed SFR, which prevents local applications in China. Considering the importance of traffic behavior (headway) in determining SFR and SLT, this study started from headway distribution and attempted to specify the relationships between headway and vehicle position directly. A common intersection in Nanjing, China, was selected to implement field study and data from 920 queues was collected. Headway distribution was explored and the 78th percentile of headway at each position was selected to build model. Based on the developed relationships, SFR and SLT were calibrated. The results showed that SFR and SLT were correlated with queue length. Moreover, the results showed that it was difficult to reach saturated state even with a long queue length. This paper provides a new perspective on calibrating important parameters in signal timing, which will be useful for traffic agencies to complete signal timing by making the process simpler. [ABSTRACT FROM AUTHOR]

Restaurants in China have recently begun offering group-buying (GB) options on the internet as a marketing and advertising tool to attract customers. GB coupon is available to parties of any size and the groups do not need to go together to the restaurants. Such restaurants serve two types of customers: GB customers with GB coupons and regular customers without coupons. One common practice for these restaurants is to set a maximum number of tables for each type of customer in advance and ask customers to wait in separate queues when all the tables for that customer type are occupied. As a result, restaurants are interested in finding optimal table allocation to serve the two types of customers to maximize profits. Since customers come follow a stochastic and discrete process, eat on a table that can be regarded as being served by a server in a queueing system, and wait in the queue when the restaurant is full, the dining process of customers and operating process of the restaurant is suitable to be described by queueing system. So, this study applies queueing theory to examine the table allocation problem. The effects of customer related parameters such as arrival rate and patience degree on the optimal allocation are discussed. The simulation model is extended to consider customers arriving in parties of different and serving tables of different sizes. We find that for a specific type of customer, if the arrival rate increases, the number of tables allocated for them increases. Patience degree has opposite influences on table allocation for the two types of customers: if regular customers are not patient, more tables should be allocated to them; while if GB customers are not patient, less tables should be allocated to them. If considering different customer party sizes and table sizes, as the arrival rate of regular customer increases, number of GB table decreases, number of tables for large (small) regular party first decreases (increases) and then increases (decreases). [ABSTRACT FROM AUTHOR]

Interindustry linkage analysis is an important interdisciplinary research field of technical economic and complex systems, and the results can be used as critical bases for making strategies and policies of economic development. This study reviews the previous methods for measuring interindustry linkages and their disadvantages and puts forward a new method for interindustry linkage analysis in a complex economic system on the basis of demand-driven and multisector input-output model. Firstly, it makes a further decomposition of the Leontief inverse matrix in the economic sense and decomposes the gross output of one industrial sector or its sub-industries into three components. Then, it analyzes the structural features of output and measures the interindustry linkages between two industrial sectors with three indices: interindustry linkage effect, interindustry linkage contribution, and interindustry linkage coefficient. Compared with the previous measurements, the method in this study has three obvious advantages: it integrates the sectoral internal effect and external linkage effect at the same time; it can not only measure the interindustry linkage effects between two given industrial sectors but also clearly describe the composition ratio of the direct and indirect interindustry linkage effects; and it adopts, respectively, the absolute flow value, relative flow value, and unit relative value to measure the linkages comprehensively. Finally, this study takes China's input and output in 2017 as an application case to analyze the structural features of output of its manufacturing and producer services and measure the interindustry linkages between them. [ABSTRACT FROM AUTHOR]

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