First-come First-served Basis Research Articles

Equilibrium arrivals to a last-come first-served preemptive-resume queue

We consider a queueing system which opens at a given point in time and serves a finite number of users according to the last-come first-served discipline with preemptive-resume (LCFS-PR). Each user must decide individually when to join the queue. We allow for general classes of user preferences and service time distributions and show existence and uniqueness of a symmetric Nash equilibrium. Furthermore, we show that no continuous asymmetric equilibrium exists, if the population consists of only two users, or if arrival strategies satisfy a mild regularity condition. For an illustrative example, we implement a numerical procedure for computing the symmetric equilibrium strategy based on our constructive existence proof for the symmetric equilibrium. We then compare its social efficiency to that obtained if users are instead served on a first-come first-served (FCFS) basis.

Clinical implementation of 177Lu-PSMA-617 (LuPSMA) at a major academic center: Initial experiences.

108 Background: LuPSMA received FDA approval in March 2022 for patients with PSMA-positive metastatic castrate-resistant prostate cancer (mCRPC). Clinical implementation of this treatment requires multidisciplinary team (MDT) involvement and has been beset by challenges in drug supply. We established a joint DFCI GU/Nuclear Medicine Tumor Board (GU-NM TB) to review patients for therapy, and our initial experiences are described. Methods: A joint GU-NM TB was established. All patients with mCRPC who had received at least one prior chemotherapy and a novel hormonal agent were considered eligible and referred to TB through an online referral system after undergoing PSMA-PET/CT. Case details, including prior treatment history, performance status and organ function, and PET/CT imaging were reviewed at TB, with patients either being approved, deferred, or declined for LuPSMA therapy. Patients were scheduled for therapy on a first-come first-served basis. Treatment was delivered per standard-of-care at 180-200 millicurie doses every 6 weeks within NM. A questionnaire was sent to 25 referring physicians 2 months after implementation of the TB to evaluate the referral process. Results: Between May-September 2022, a total of 108 patients were referred for LuPSMA therapy. Median age at time of referral was 73 (range 52-93), and 90% of patients were Caucasian. Median duration between PSMA-PET/CT and TB review was 10 days (IQR 6-17). 84 patients (78%) were approved for therapy, 16 (15%) were deferred and 7 (6%) were declined (reasons including absence of prior chemotherapy, high risk for toxicities, poor performance status); 1 patient died before TB review. Prior therapies included docetaxel (84%), cabazitaxel (56%), abiraterone (67%), enzalutamide (57%), darolutamide (23%), radium-223 (21%) and apalutamide (7%). Median number of prior treatments was 4 (range 2-12). Sites of disease on PSMA-PET/CT included bone (81%), pelvic lymph nodes (42%), extrapelvic lymph nodes (88%), lung (27%) and liver (22%). As of September 2022, a total of 40 patients (48%) have received at least 1 cycle of therapy and 17 (20%) have received 2 cycles; 6 patients (7%) approved for therapy died before receiving 177Lu-PSMA-617. Of the patients that have received 1 cycle of therapy, median duration between TB acceptance and C1 was 52 days (range 32-114). Out of 13 survey respondents, all 13 (100%) reported that their overall experience of the referral process was positive or very positive, and 12 (92%) noted that the Tumor Board had provided additional clinical insights on occasion or frequently. Conclusions: Due to drug supply shortages, <50% of patients approved for LuPSMA therapy have started treatment to date. Median time between TB approval and start of therapy was 7-8 weeks, with 7% of patients dying before receiving therapy. Establishment of a GU-NM TB to review cases and facilitate treatment was viewed favorably by treating physicians.

Discrete-time strategic job arrivals to a single machine with waiting and lateness penalties

A single machine processes a random number of identical jobs on a first-come first-served (FCFS) basis. Processing times are independent and identically distributed with a general integral distribution. Each job is held by a strategic player who needs to choose a time slot to arrive at. The individual objective is to reduce the sum of two types of linear in time costs: lateness and waiting. The resulting decision making model is, then, a symmetric non-cooperative game. We derive a symmetric Nash equilibrium for this game, and discuss its structural properties.

How Should ECMO Be Used Under Conditions of Severe Scarcity? A Population Study of Public Perception

ObjectiveTo assess societal preferences regarding allocation of extracorporeal membrane oxygenation (ECMO) as a rescue option for select patients with coronavirus disease 2019 (COVID-19).DesignCross-sectional survey of a nationally representative sample.SettingAmazon Mechanical Turk platform.ParticipantsIn total, responses from 1,041 members of Amazon Mechanical Turk crowd-sourcing platform were included. Participants were 37.9 ± 12.6 years old, generally white (65%), and college-educated (66.1%). Many reported working in a healthcare setting (22.5%) and having a friend or family member who was admitted to the hospital (43.8%) or died from COVID-19 (29.9%).Measurements and Main ResultsAlthough most reported an unwillingness to stay on ECMO for >one week without signs of recovery, participants were highly supportive of ECMO utilization as a life-preserving technique on a policy level. The majority (96.7%) advocated for continued use of ECMO to treat COVID patients during periods of resource scarcity but would prioritize those with highest likelihood of recovery (50%) followed by those who were sickest regardless of survival chances (31.7%). Patients >40 years old were more likely to prefer distributing ECMO on a first-come first-served basis (21.5% v 13.3%, p < 0.05).ConclusionEven though participants expressed hesitation regarding ECMO in personal circumstances, they were uniformly in support of using ECMO to treat COVID patients at a policy level for others who might need it, even in the setting of severe scarcity.

Strategic arrivals to a queue with service rate uncertainty

We study the problem of strategic choice of arrival time to a single-server queue with opening and closing times when there is uncertainty regarding service speed. A Poisson population of customers choose their arrival time with the goal of minimizing their expected waiting times and are served on a first-come first-served basis. There are two types of customers that differ in their beliefs regarding the service-time distribution. The inconsistent beliefs may arise from randomness in the server state along with noisy signals that customers observe. Customers are aware of the two types of populations with differing beliefs. We characterize the Nash equilibrium dynamics for exponentially distributed service times and show how they substantially differ from the model with homogeneous customers. We further provide an explicit solution for a fluid approximation of the game. For general service-time distributions we provide an algorithm for computing the equilibrium in a discrete-time setting. We find that in equilibrium customers with different beliefs arrive during different (and often disjoint) time intervals. Numerical analysis further shows that the mean waiting time increases with the coefficient of variation of the service time. Furthermore, we present a learning agent-based model (ABM) in which customers make joining decisions based solely on their signals and past experience. We numerically compare the long-term average outcome of the ABM with that of the equilibrium and find that the arrival distributions are quite close if we assume (for the equilibrium solution) that customers are fully rational and have knowledge of the system parameters, while they may greatly differ if customers have limited information or computing abilities.

A gender-sensitised weight-loss and healthy living program for men with overweight and obesity in Australian Football League settings (Aussie-FIT): A pilot randomised controlled trial.

Recent evidence shows that sport settings can act as a powerful draw to engage men in weight loss. The primary objective of this pilot study was to test the feasibility of delivering and to evaluate preliminary efficacy of Aussie-FIT, a weight-loss program for men with overweight/obesity delivered in Australian Football League (AFL) settings, in preparation for a future definitive trial. This 6-month pilot trial took place in Perth, Australia. Participants were overweight/obese (Body Mass Index [BMI] ≥ 28 kg/m2), middle-aged (35-65 years old) men. Participants were recruited in May 2018, and the intervention took place between June and December 2018. The intervention involved 12 weekly 90-min face-to-face sessions, incorporating physical activity, nutrition, and behaviour change information and practical activities delivered by coaches at 2 clubs. Data were collected at baseline and immediately postintervention. For trial feasibility purposes, 6-month follow-ups were completed. Outcomes were differences in weight loss (primary outcome) and recruitment and retention rates, self-reported measures (for example, psychological well-being), device-measured physical activity, waist size, and blood pressure at 3 months. Within 3 days of advertising at each club, 426 men registered interest; 306 (72%) were eligible. Men were selected on a first-come first-served basis (n = 130; M age = 45.8, SD = 8; M BMI = 34.48 kg/m2, SD = 4.87) and randomised by a blinded researcher. Trial retention was 86% and 63% at 3- and 6-month follow-ups (respectively). No adverse events were reported. At 3 months, mean difference in weight between groups, adjusted for baseline weight and group, was 3.3 kg (95% CI 1.9, 4.8) in favour of the intervention group (p < 0.001). The intervention group's moderate-to-vigorous physical activity (MVPA) was higher than the control group by 8.54 min/day (95% CI 1.37, 15.71, p = 0.02). MVPA among men attracted to Aussie-FIT was high at baseline (intervention arm 35.61 min/day, control arm 38.38 min/day), which may have limited the scope for improvement. Aussie-FIT was feasible to deliver; participants increased physical activity, decreased weight, and reported improvements in other outcomes. Issues with retention were a limitation of this trial. In a future, fully powered randomised controlled trial (RCT), retention could be improved by conducting assessments outside of holiday seasons. Australian New Zealand Clinical Trials Registry: ACTRN12617000515392.

A discrete-time single-server Poisson queueing game: Equilibria simulated by an agent-based model

This paper considers a discrete-time single-server queue with a single acceptance period for a Poissonian population of homogeneous customers. Customers are served on a first-come first-served (FCFS) basis, and their service times are independent and identically distributed with a general distribution. We assume that each customer chooses her/his arrival-time slot with the goal of minimizing her/his expected waiting time in competition with other customers. For this queueing game, we derive a symmetric (mixed-strategy) Nash equilibrium; that is, an equilibrium arrival-time distribution of homogeneous customers, where their expected waiting times are identical. We also propose an agent-based model, which simulates the dynamics of customers who try to minimize their waiting times for service. Through numerical experiments, we confirm that this agent-based model achieves, in steady state, an arrival-time distribution similar to the equilibrium arrival-time distribution analytically obtained.

On first-come, first-served queues with two classes of impatient customers

We study systems with two classes of impatient customers who differ across the classes in their distribution of service times and patience times. The customers are served on a first-come, first-served basis (FCFS) regardless of their class. Such systems are common in customer call centers, which often segment their arrivals into classes of callers whose requests differ in their complexity and criticality. We first consider an M/G/1 + M queue and then analyze the M/M/k + M case. Analyzing these systems using a queue length process proves intractable as it would require us to keep track of the class of each customer at each position in the queue. Consequently, we introduce a virtual waiting time process where the service times of customers who will eventually abandon the system are not considered. We analyze this process to obtain performance measures such as the percentage of customers receiving service in each class, the expected waiting times of customers in each class, and the average number of customers waiting in queue. We use our characterization to perform a numerical analysis of the M/M/k + M system and find several managerial implications of administering a FCFS system with multiple classes of impatient customers. Finally, we compare the performance a system based on data from a call center with the steady-state performance measures of a comparable M/M/k + M system. We find that the performance measures of the M/M/k + M system serve as good approximations of the system based on real data.

Would You Like A Free Mammogram? Effectiveness of Utilizing WhatsApp As a Social Marketing Tool in Improving Uptake for a Free Mammography Service in Kuala Lumpur Malaysia

Background: Social media and messaging services are increasingly targeted by health providers as an avenue to spread health messages, increase awareness and also for social marketing. WhatsApp is a social media application which has wide penetration in Malaysia, with more than half the population relying on WhatsApp for news. Aim: This study aimed to determine the effectiveness of WhatsApp as a social marketing tool to increase uptake for a free mammography service for underprivileged women. Methods: This was a randomized clinical trial conducted in Kuala Lumpur, Malaysia. Individuals from the National Cancer Society of Malaysia database were randomized into 1 of 3 arms receiving a WhatsApp message; i) a poster of a free mammography service for underprivileged women; ii) a poster of the free mammography service for underprivileged women with a personal message from the Director of the National Cancer Society of Malaysia; and iii) the poster, personal message from the director and a specific Saturday screening date with the exhortation that there were only 40 places available for that date on a first-come first-serve basis. The outcomes of the trial were i) number of women who returned a call or WhatsApp message to the designated numbers; ii) number of women who booked an appointment for the mammography service; and iii) numbers of women who attended the appointment. Results: The number of calls and inquiries to designated numbers increased by more than 200% as a result of the WhatsApp messages. There were statistically significant differences between the three delivery arms; with the highest percentages of women booking and attending their mammography appointments coming from the arm which had a designated screening date with limited availability. Conclusion: WhatsApp was highly effective at increasing community penetration and marketing a free mammography service for underprivileged women in Kuala Lumpur. Messages with an appeal from a personage and with a specific date of “expiry” were more effective at getting the targeted group to avail themselves of the service.

A continuous cost evaluation approach for periodic review inventory systems with threshold rationing policy

Abstract This study analyzes an inventory problem with two stochastic demand classes in a periodic review inventory setting, in which a firm reviews its inventory position periodically and fulfills two Poisson demand classes continuously during periods. This study simultaneously assumes positive lead time and full backorders. An inventory policy consisting of order-up-to policy and threshold rationing policy is adopted, in which the firm places an order to raise its inventory position to order-up-to level in a fixed length of review interval and the inventory is rationed with a threshold level. Specifically, the total demand is served on a first-come first-served basis (FCFS) if its available inventory is above the threshold level. Otherwise, only the high-priority demand class is served. With such an inventory policy, this study provides a novel approach to evaluate the exact long-run expected inventory costs by assuming a threshold backorder clearing mechanism. This evaluation approach can easily incorporate FCFS policy. Furthermore, a method is provided to find the optimal policy parameters. Numerical experiments show that, relative to the FCFS policy and separate policy, the rationing policy can generate significant cost savings.

Equilibrium Arriaval Times to Queues: The Case of Last-Come First-Serve Preemptive-Resume

We consider a non-cooperative queueing environment where a finite number of customers independently choose when to arrive at a queueing system that opens at a given point in time and serves customers on a last-come first-serve preemptive-resume (LCFS-PR) basis. Each customer has a service time requirement which is identically and independently distributed according to some general probability distribution, and they want to complete service as early as possible while minimizing the time spent in the queue. In this setting, we establish the existence of an arrival time strategy that constitutes a symmetric (mixed) Nash equilibrium, and show that there is at most one symmetric equilibrium. We provide a numerical method to compute this equilibrium and demonstrate by a numerical example that the social efficiency can be lower than the efficiency induced by a similar queueing system that serves customers on a first-come first-serve (FCFS) basis.

Pricing and Matching with Forward-Looking Buyers and Sellers

Motivated by the emerging sharing economy, we study a dynamic market of a single product or service, to which buyers with heterogeneous private valuations and sellers with heterogeneous private supply costs sequentially arrive following Poisson processes. A single market making intermediary dynamically decides on the ask and bid prices posted to buyers and sellers, respectively, and on the matching decisions after buyers and sellers agree to buy and sell, respectively. Buyers and sellers can strategically wait for better prices after their arrivals. The intermediary’s problem is a multi-dimensional mechanism design problem that is hard to analyze. We propose a simple heuristic policy, that is, a fixed ask price charged to the buyers and a fixed bid price offered to the sellers plus a price adjustment as compensation for expected waiting cost, in conjunction with the greedy matching policy on a first-come first-served basis. These fixed base prices balance demand and supply in expectation, and can be computed efficiently. The waiting adjusted ask and bid price processes are time dependent and tend to have opposite trends in the beginning and end of the horizon. Under this heuristic policy, forward-looking buyers and sellers behave myopically without wait. We show that this heuristic policy is asymptotically optimal for the intermediary and the waiting time compensation becomes negligible, as the volumes of demand and supply arrivals proportionally grow. Our results suggest that the random arrivals of heterogeneous buyers and sellers, alone, may not be sufficient to justify contingent pricing. Given Uber changes its prices every five minutes to rapidly micro-match supply with demand, our result suggests Uber may not lose much optimality by reducing the frequency of price changes, unless the underlying market conditions have significantly changed. This is because our fixed pricing has captured the first-order effect and the benefit of surge pricing diminishes as the volumes of the platform grow, not to mention frequent surge pricing may agonize riders and induce strategic behaviors of riders and drivers that are hard to account for.

Exact Analysis of Divergent Inventory Systems with Time-Based Shipment Consolidation and Compound Poisson Demand

Sustainable and efficient management of a distribution system requires coordination between transportation planning and inventory control decisions. In this context, we consider a one warehouse multi-retailer inventory system with a time-based shipment consolidation policy at the warehouse. This means that there are fixed costs associated with each shipment, and retailer orders are consolidated and shipped periodically to groups of retailers sharing the same delivery routes. Customer demand is compound Poisson distributed and unsatisfied demand at each stock point is backordered and allocated on a first-come first-served basis. The system is centralized and inventory levels are reviewed continuously. The warehouse has access to real-time inventory information from the retailers, and uses a (R, nQ) policy to replenish from an outside supplier/manufacturer. We derive the exact probability distributions for the inventory levels at the retailers, and use these to obtain exact expressions for the system’s expected shipment, holding and backorder costs, its average inventory levels, and fill rates. Based on the analytical properties of the objective function, we construct an optimization procedure by deriving bounds on the optimal reorder levels and shipment intervals both for single-item and multi-item systems.

Establishing a National Emergency Department Surveillance: an innovative study from Pakistan.

Establishing a National Emergency Department Surveillance: an innovative study from Pakistan.

Efficient Cloud Computing for Scientific Communities: Design and Implementation

The main purpose of cloud system is to provide the unlimited computing and storage resources. This paper describes that existing DawningCloud is an efficient cloud system for scientific communities. DawningCloud provides efficient resource management and provisioning policy. DawningCloud gave the concepts of Enhanced Scientific Public cloud and also included the concepts of runtime environment of PhoenixCloud. However, this system didn’t investigate the effect of different scheduling policy. DawningCloud simply used First Come First Served (FCFS) scheduling Policy and didn’t investigate the effect of different scheduling techniques on them. Therefore, we proposed a new cloud system for scientific communities. This proposed science cloud included the concept of DawningCloud and novel Earlier Account Expire Prioritized with Round Robin (EAEP-RR) scheduling technique. This paper describes the design and implementation of proposed Science Cloud. However, this scheduling method provides benefits only to the earlier account expiration user. Remaining users served as a FCFS basis. General Terms Cloud Computing, Scientific Community, Runtime environment (RTE), Earlier Account Expire Prioritized with Round Robin (EAEP-RR) scheduling

Smartphone Response System Using Twitter to Enable Effective Interaction and Improve Engagement in Large Classrooms

This paper proposes a method for seamless interaction between students and their professor using Twitter, one of the typical social network service (SNS) platforms, in large lectures. During the lecture, the professor poses surprise questions in the form of a quiz on an overhead screen at unexpected moments, and students submit their answers through a smartphone response system using Twitter. Since points are awarded on a first-come–first-served basis to only a limited number of the students who submit correct answers, students are required to concentrate on the lecture if they want to score. The proposed method solves both the problem of decreased concentration arising from frequent use of smartphones for nonlearning purposes in lectures and of inefficient interaction that occurs in large university classrooms. Evaluation through analysis of exam results and a post-course survey confirm that the proposed solution produces better results in terms of both students' academic achievement and their concentration during lectures.

Spare parts provisioning for multiple k-out-of-n:G systems

This article considers a repair shop that fixes failed components from different k-out-of-n:G systems. It is assumed that each system consists of the same type of component; to increase availability, a certain number of critical components are stocked as spare parts. A shared inventory that serves all systems and/or reserved inventories for each system are allowed; this is called a hybrid model. Additionally, two alternative dispatching rules for the repaired component are considered. The destination for a repaired component can be chosen either on a first-come first-served basis or by following a static priority rule. The analysis gives the steady-state system size distribution of the two alternative models at the repair shop. Numerical examples are performed that minimize the spare parts held while subjecting the availability of each system to exceed a targeted value. It is shown that a hybrid priority policy is better than a hybrid first-come first-served policy, unless the availabilities of systems are close.

A periodic-review inventory control policy for a two-level supply chain with multiple retailers and stochastic demand

We consider a time-based inventory control policy for a two-level supply chain with one warehouse and multiple retailers in this paper. Let the warehouse order in a fixed base replenishment interval. The retailers are required to order in intervals that are integer-ratio multiples of the base replenishment interval at the warehouse. The warehouse and the retailers each adopt an order-up-to policy, i.e. order the needed stock at a review point to raise the inventory position to a fixed order-up-to level. It is assumed that the retailers face independent Poisson demand processes and no transshipments between them are allowed. The contribution of the study is threefold. First, we assume that when facing a shortage the warehouse allocates the remaining stock to the retailers optimally to minimize system cost in the last minute before delivery and provide an approach to evaluate the exact system cost. Second, we characterize the structural properties and develop an exact optimal solution for the inventory control system. Finally, we demonstrate that the last minute optimal warehouse stock allocation rule we adopt dominates the virtual allocation rule in which warehouse stock is allocated to meet retailer demand on a first-come first-served basis with significant cost benefits. Moreover, the proposed time-based inventory control policy can perform equally well or better than the commonly used stock-based batch-ordering policy for distribution systems with multiple retailers.

Screening for chronic kidney diseases among an adult population

Chronic kidney disease (CKD) is now one of the major health problems all over the world and its early screening is vital to prevent the development of end-stage renal failure. This study was designed to evaluate the proportion of urban adults suffering from CKD as well as to have a preliminary idea about the determinants of this disorder. The screening program for CKD was arranged in a public place in Dhaka city, Bangladesh, and involved 634 adult participants (>18 years of age) selected on first-come first-served basis. Socio-demographic, anthropometric, and clinical data were collected. Urinary protein was tested by the dipstick method, and serum glucose and creatinine were measured by an auto-analyzer. Estimated glomerular filtrate rate (eGFR) was calculated by using standard formula. CKD was diagnosed and classified according to the National Kidney Foundation (NKF) Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines. A total of 12.8% of the subjects were found to have CKD of whom 2.7% were in Stage 1, 4.1% in Stage 2, and 6% were in Stage 3. The proportion was strongly influenced by age, with the highest prevalence (38.5%) found at 60 years and above. The CKD group showed higher body mass index, waist-hip ratio, and systolic blood pressure, compared with their non-CKD counterparts (P = 0.02). On multiple regression analysis (after adjustment of some confounding variables), age, random blood sugar, and education showed significant association with the development of CKD. A substantial number of urban adults in Dhaka were found to be unaware about the existence of CKD and large-scale prevention programs should be undertaken to reduce the classical risk factors of these disorders.

Regulation for renewable energy development: Lessons from Sri Lanka experience

The paper examines the key features of the renewable energy development environment in Sri Lanka which led to sector's rapid expansion. The recent development framework of the renewable energy sector was based on the importance of using indigenous resources, recognizing the positive environmental impacts and the avoidance of high cost alternative thermal generation. This framework also recognized the pioneering effort of the developers in site identification by giving rights to develop on a first-come first-served basis. The policy framework was later extended with a renewable energy portfolio standard to achieve 10% of power generation through renewable energy. The standard power purchase arrangements reduced the transaction costs. The feeding tariffs originally based on avoided costs later shifted to cost based, technology specific tariffs encouraging diversification of the renewable energy portfolio. The introduction of net-metering for renewable energy based distributed generation and the limited interventions in the form of green-tariffs also assisted the renewable energy development. The paper concludes that the policy and regulatory frameworks and different approaches to implementing them have been mostly successful experiences in Sri Lanka and they would provide useful lessons for similar countries when formulating and implementing related polices, regulations and legal frameworks.