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This study is carried out in one public and one private health-care centers based on different probabilities of patient’s no-show rate. The present study aims to determine the optimal queuing system capacity so that the expected total cost is minimized.

In this study an M/M/1/K queuing model is used for analytical properties of optimal queuing system capacity and appointment window so that total costs of these cases could be minimized. MATLAB software version R2014a is used to code the model.

In this paper, the optimal queuing system capacity is determined based on the changes in effective parameters, followed by a sensitivity analysis. Total cost in public center includes the costs of patient waiting time and rejection. However, the total cost in private center includes costs of physician idle time plus costs of public center. At the end, the results for public and private centers are compared to reach a final assessment.

Today, determining the optimal queuing system capacity is one of the most central concerns of outpatient clinics. The large capacity of the queuing system leads to an increase in the patient’s waiting-time cost, and on the other hand, a small queuing system will increase the cost of patient’s rejection. The approach suggested in this paper attempts to deal with this mentioned concern.

This paper aims to investigate the optimal price and service rate decisions in a customer-intensive service, where customers’ perceived service quality decreases in the service speed. Customers are assumed to be forward-looking in purchase decision-making and heterogeneous in their reservation utilities. The purpose of this paper is to study the impact of customers’ forward-looking behavior and the heterogeneity on the operational decisions in a customer-intensive context.

The service is delivered through an M/M/1 queue system with unobservable queues. Customers are forward-looking in queue joining decisions, where the purchase decisions are made when the expected utility is greater than the reservation utility. The optimal price and service rate decisions are analyzed with both homogeneous and heterogeneous customers, where homogenous customers have the same reservation utility in purchase decision-making, while heterogeneous customers have different reservation utilities, which are captured by a random variable.

The optimal price and service rate decisions with forward-looking customers depend on the customer intensity, potential market size and customers’ reservation utility distribution. The results suggest that customers’ heterogeneity in terms of their reservation utilities affects the optimal decisions, market coverage and the expected revenue. Service providers need to take customers’ heterogeneity and the forward-looking behavior into operational decision-making.

This paper extends previous studies in customer-intensive service and contribute to the service operations management area by explicitly incorporating customers’ forward-looking behavior and heterogeneity in purchase decision-making. Assuming customers are forward-looking and heterogeneous is more realistic and practical. The results highlight that knowing customers’ behavioral characteristics can better improve decision-making in service operations, which is critical for enhancing customers’ satisfaction and loyalty, thus critical to a firm’s success in the market with intensive competition.

The purpose of this paper is to propose a method to determine the optimal number of operators to be assigned to a given number of machines, as well as the number of machines that will be run by each operator (a numerical partition). This determination should be made with the objective of minimizing production costs or maximizing profits.

The method calculates the machines interference rate via the binomial distribution function. The optimal assignment is calculated by transformation of a partition problem into a problem of finding the shortest path on a directed acyclic graph.

The method enables the authors to calculate the adjusted cycle time, the workload of the operators, and the utility of the machines, as well as the production yield, the total cost per unit, and the hourly profit for each potential assignment of operators to machines. In a case study, the deviation of the output per hour of the proposed method from the actual value was about 2 percent.

The paper provides formulas and tables that give machine interference rates through the application of binomial distribution. The practicability of the proposed method is demonstrated by a real-life case study.

The method can be applied in a wide variety of manufacturing systems that use many identical machines. This includes tire presses in tire manufacturing operations, ovens in pastry manufacturing systems, textile machines, and so on.

The purpose of this paper is to show how elements from queueing theory can be used to obtain objective measures of effective capacity in the triage function at Skaraborg Hospital in Sweden without direct observation of the function itself.

Approximately 30,000 patients arrived to the emergency department at Skaraborg Hospital in Sweden during 2011. The exact time of arrival and the exact time of triage were recorded for each patient on an individual level. Basic queueing theory uses arrival rates and system capacity measures to derive average queueing times. The authors use the theoretical relation between these three measures to derive system capacity measures based on observed arrival rates and observed average queueing times.

The effective capacity in the triage process is not a linear function of the number of nurses. However, the management of capacity seems well adapted to the actual demand, even though service levels vary substantially during the day and night.

This paper uses elements from queueing theory in an innovative way to measure the effective capacity of a service process without direct observation, thereby also avoiding the potential risk of the Hawthorne effect.

This paper aims to focus on production ramp up modeling on built‐to‐order (BTO) manufacturers facing customized demand. The general purpose is to present a novel approach to managing collaboration, by considering information exchange between the manufacturer and the supplier.

The methodology applies feedback control mechanism to analyze supplier responsiveness and customer order decoupling point to represent the need for collaboration. A two‐stage game is applied ahead of control system application to optimize the capacity decision, with the ultimate goal being profit maximization.

The results show that a higher product commonality degree gives more opportunity for quick response BTO supply chains, which are managed by feedback control, and at the same time to possibly mitigate the bullwhip effect caused by demand information noise.

The analytical model here focused on one product family development, so the applicability of the proposed model to the whole product portfolio should be investigated in the future.

This paper helps the manufacturer to act optimally by considering the possibility of information exchange with the supplier and deciding on the product commonality degree, in taking into account the customer's lead time requirement.

A control system model of “BTO Supply Chain” is proposed by including product commonality and response analysis in the simulation model. Furthermore, a contribution to collaborative supply chains is shown by applying a synchronized supply model to represent supplier and manufacturer communication.

The duration of an urban search and rescue (USAR) operation directly depends on the number of rescue teams involved. The purpose of this paper is to simplify the earthquake environment and determine the initial number of rescuers in earthquake emergencies in USAR operation.

In the proposed methodology, four primary steps were considered: evaluation of buildings damage and the number of injured people by exerting geospatial information system (GIS) analyses; determining service time by means of task allocation; designing the simulation model (queuing theory); and calculation of survival rate and comparison with the time of rescue operations.

The calculation of buildings damage for an earthquake with 6.6 Richter in Tehran’s District One indicated that 18% of buildings are subjected to the high damage risk. The number of injured people calculated was 28,856. According to the calculated survival rate, rescue operations in the region must be completed within 22.33 h to save 75% of the casualties. Finally, the design of the queue model indicated that at least 2,300 rescue teams were required to provide the calculated survival rate.

The originality of this paper is an innovative approach for determining an appropriate number of rescue teams by considering the queuing theory. The results showed that the integration of GIS and the simulation of queuing theory could be a helpful tool in natural disaster management, especially in terms of rapid vulnerability assessment in urban districts, the adequacy and appropriateness of the emergency services.

Customer-intensive services refer to the service that a provider needs to invest in customers with high patience and experience. Within a certain rate range, the slower service rate and the longer service time, the higher customer’s utility; however, this may cause queue congestion. And the advertising of service provider will affect the revenue. The purpose of this paper is to investigate the effects of advertising on the optimal price, service rate and the optimal revenue of such service provider at different development stages.

This paper investigates the service strategies of service provider based on advertising effects. The authors first divide service provider into insufficient customers or sufficient customers according to the development stage, then analyze the impact of advertising at different stages. The authors focus on the formulation of the optimal price, service rate and the optimal revenue of service provider at different stages.

This paper finds that in the insufficient customers stage, the service provider’s strategy of “small profits but quick turnover” is conducive to quickly accumulating customers. With the development of service provider, the advertising indirectly increases the revenue of service provider by maintaining popularity. The result also shows that with the development of service provider, the initiative of such service market has gradually been mastered by service provider, from “buyer market” to “seller market.”

The finding provides an alternative explanation for the impact of advertising on service provider’s optimal strategies; it also solves the settings of service price and rate of customer-intensive service provider at different development stages. This study is essential to create the optimal revenue and solve supply–demand conflicts (such as doctor–patient conflict) between service provider and customers.

This paper aims to consider a single server queue with system disasters and impatience behavior are evident in our daily life. For this purpose, authors require to know the general behavior of these systems. Transient analysis shows for us how the system will operate up to some time instant t.

In this paper, authors consider a single server queue with system disaster and impatient behavior of customers in a multi-phase random environment, in which the system transits to a repair state after each system disaster. When the system is in a failure phase or going through a repair phase, the new arrivals would be impatient. In case the system is not repaired before the customer’s time expires, the customer would leave the queue and never return. Moreover, after repair, the system becomes ready for service in an operative phase with probability $q_{i} \ge 0.$. Using generating functions along with continued fractions and some properties of the confluent hypergeometric function, authors obtained on their own results.

Explicit expressions have been obtained for the time-dependent probabilities of the underlying queuing model. Also, time-dependent mean and variance of customers in the system are deduced.

The system authors are dealing with is somewhat complicated, there are some performance measures that cannot be achieved, but some of them have been obtained, such as the expectation and variance of the number of customers in the system.

Based on the obtained results, some numerical examples are some numerical examples are presented to illustrate the effect of various parameters on the behavior of the proposed system.

Authors’ studied transient analysis of a single server queue with system disaster and impatient customer system is suitable for behavior interpretation of many systems in our lives, such as telecommunication networks, inventory systems and impatient telephone switchboard customers, manufacturing system and service system.

To the best of the author’s/authors’ knowledge and according to the literature survey, in a multi-phase random environment, no previous published article is presented for transient analysis of a single server queue with system disaster and impatient customer behavior in a random environment.

The main purpose of this paper is to present a comprehensive upscale theory of the thermo-mechanical coupling particle simulation for three-dimensional (3D) large-scale non-isothermal problems, so that a small 3D length-scale particle model can exactly reproduce the same mechanical and thermal results with that of a large 3D length-scale one.

The objective is achieved by following the scaling methodology proposed by Feng and Owen (2014).

After four basic physical quantities and their similarity-ratios are chosen, the derived quantities and its similarity-ratios can be derived from its dimensions. As the proposed comprehensive 3D upscale theory contains five similarity criteria, it reveals the intrinsic relationship between the particle-simulation solution obtained from a small 3D length-scale (e.g. a laboratory length-scale) model and that obtained from a large 3D length-scale (e.g. a geological length-scale) one. The scale invariance of the 3D interaction law in the thermo-mechanical coupled particle model is examined. The proposed 3D upscale theory is tested through two typical examples. Finally, a practical application example of 3D transient heat flow in a solid with constant heat flux is given to illustrate the performance of the proposed 3D upscale theory in the thermo-mechanical coupling particle simulation of 3D large-scale non-isothermal problems. Both the benchmark tests and application example are provided to demonstrate the correctness and usefulness of the proposed 3D upscale theory for simulating 3D non-isothermal problems using the particle simulation method.

The paper provides some important theoretical guidance to modeling 3D large-scale non-isothermal problems at both the engineering length-scale (i.e. the meter-scale) and the geological length-scale (i.e. the kilometer-scale) using the particle simulation method directly.

The purpose of this paper is to provide a traffic route selection strategy based on minimum carbon dioxide (CO₂) emission by vehicles over different route choices.

The study used queuing theory for Markovian M/M/1 model over the road junctions to assess total time spent over each of the junctions for a route with junctions in tandem. With parameters of distance, mean service rate at the junction, the number of junctions and fuel consumption rate, which is a function of variable average speed, the CO₂ emission is estimated over each of the junction in tandem and collectively over each of the routes.

The outcome of the study is a mathematical formulation, using queuing theory to estimate CO₂ emissions over different route choices. Research finding estimated total time spent and subsequent CO₂ emission for mean arrival rates of vehicles at junctions in tandem. The model is validated with a pilot study, and the result shows the best vehicular route choice with minimum CO₂ emissions.

Proposed study is limited to M/M/1 model at each of the junction, with no defection of vehicles. The study is also limited to a constant mean arrival rate at each of the junction.

The work can be used to define strategies to route vehicles on different route choices to reduce minimum vehicular CO₂ emissions.

Proposed work gives a solution for minimising carbon emission over routes with unsignalised junctions in the tandem network.