Scheduling Table Research Articles

Research on the Optimization Method of Bus Travel Safety Considering Drivers’ Risk Characteristics

Bus drivers have an important role in ensuring road safety, as their driving circumstances fluctuate due to the combined influence of physiological, psychological, and environmental dynamics, which can cause complex and varied driving dangers. Quantifying and assessing drivers’ risk characteristics under various scenarios, as well as finding the best fit with their work schedules, is critical for enhancing bus safety. This research first uses the entropy weight method, which is based on historical warning data, to examine the risk characteristics of bus drivers in various complicated contexts. It then creates an objective function targeted at minimizing the operational risk for a specific bus route. This function uses the quasi-Vogel approach and an improved simulated annealing algorithm to optimize and restructure the scheduling table, taking individual driver risk characteristics into account. Finally, the analysis is confirmed and examined with actual operational data from the Zhenjiang Bus Line 3. The data show that enhanced bus operations resulted in a 7.22% gain in overall safety and a 33.76% improvement in balancing levels. These insights provide valuable theoretical guidance as well as practical references for the safe operation and administration of public buses.

A conflict-free CAN-to-TSN scheduler for CAN-TSN gateway

The automotive Electrical/Electronic (E/E) architecture with Time-Sensitive Networking (TSN) as the backbone network and Controller Area Network (CAN) as the intra-domain network has attracted extensive research attention. In this architecture, the CAN-TSN gateway serves as a vital hub for communication between the CAN and TSN networks. However, with frequent information exchange between domains, multiple real-time applications inevitably compete for the same network resources. The limited availability of schedule table entries and bandwidth allocation pose challenges in scheduling design. To mitigate the transmission conflicts at the CAN-TSN gateway, this paper proposes a CAN-to-TSN scheduler consisting of two primary stages. The first stage introduces the Message Aggregation Optimization (MAO) algorithm to aggregate multiple CAN messages into a single TSN message, ultimately decreasing the communication overhead and the schedule table entries number. The second stage proposes the Exploratory Message Scheduling Optimization (EMSO) algorithm based on MAO. EMSO disaggregates and reassembles the CAN messages with small deadlines within the currently un-scheduled TSN message to improve the acceptance ratio of CAN messages. Experimental results demonstrate that EMSO achieves an average acceptance ratio of CAN messages 4.3% higher in preemptive mode and 8.2% higher in non-preemptive mode in TSN than state-of-the-art algorithms.

Research on the Construction Method of Real-time Scheduling Process and Bus Scheduling Table based on WorldFIP Fieldbus

The WorldFIP protocol is the third part of the European standard EN-50150. It is particularly suitable for use in distributed computer control systems. WorldFIP provides data transfer services for variable exchange, and in order to cope with the real-time requirements of the system during variable transfer, the WorldFIP protocol provides communication services based on periodic and non-periodic identification exchanges, in which periodic exchanges have the highest priority and are scheduled cyclically according to the bus scheduling table at runtime. execution at runtime according to the bus scheduling table. Therefore, when constructing the scheduling table, the respective schedulability can be determined at pre-run time. For acyclic variable exchanges, the situation is different as they have a lower priority level and perform variable exchanges according to a first-come-first-served strategy. In this paper, from the perspective of variable exchange, we study the communication mode of the WorldFIP protocol, the process of cyclic and acyclic variable exchange, introduce a method for constructing bus scheduling tables based on microcycles and macrocycles, and finally give specific examples to prove the rationality of this method.

Time-triggered scheduling of mixed-critical flows at end-system in asynchronous AFDX avionic network

Avionics Full-DupleX (AFDX) is a switched Ethernet-based network used in modern commercial airplanes for the transmission of command and control avionics flows. These critical flows require deterministic guarantees leading to a lightly loaded network. Aircraft manufacturers envision to carry additional non avionics flows (i.e. video, audio, service) to take advantage of the spare bandwidth. However, it is then compulsory to preserve the real-time guarantees of avionics flows in terms of bounded jitter at the transmitter output and of bounded end-to-end latency. Depending on the type of additional traffic, Quality of Service (QoS) end-to-end guarantees may be offered to the additional flows of lower criticality in terms of reduced delay or bounded jitter for instance. These guarantees can be ensured by scheduling policies at transmitter and switch level. However, an important safety-related constraint is the asynchronous design of avionics distributed systems that prohibits the use of a network-wide synchronization of end systems and switches. Thus, time-triggered networking such as emerging Time-Triggered Ethernet (TTEthernet) or Time-Sensitive Networking (TSN) cannot be leveraged. This paper underlines the benefits of only scheduling flows at the transmitter, which is compatible with the asynchronous safety constraint of avionics systems. We show that it is possible to build a table schedule that carries both critical avionics flows and additional video flows that meet their timing and bandwidth allocation constraints. Therefore, we design scheduling strategies for efficient distribution of flows in the table scheduling whose performance is compared to the optimal schedule minimizing the emission lag of additional flows. Proposed heuristics are constructed such as to favor the network responsiveness for avionics flows thanks to slot over-provisioning. Extensive results on an A350 AFDX industrial configuration show that for a transmitter load of up to 70% of the available bandwidth, the uniform allocation heuristic provides a performance close to optimal in terms of minimum emission lag for additional flows, so offering a practical configuration heuristic to industry.

A Mixed-Criticality Traffic Scheduler with Mitigating Congestion for CAN-to-TSN Gateway

The network architecture that Time-Sensitive Networking (TSN) is used as the backbone network and the Controller Area Network (CAN) serves as the intra-domain network is considered as the CAN-TSN interconnection network architecture, which has gained considerable attention within industrial embedded networks, such as spacecraft, intelligent automobiles, and factory automation. The architecture employs the CAN-TSN gateway as a central hub for transmitting and managing a significant volume of communications between the CAN domains and TSN. However, the CAN-TSN gateway faces a high congestion challenge due to the rapid growth in data volume, making it difficult to effectively support different time planning mechanisms provided by TSN. In this paper, we propose a two-stage mixed-criticality traffic scheduler. The scheduler in the first stage adopts a Message Optimization Algorithm (MOA) to aggregate multiple CAN messages into a single TSN message (including the aggregation of critical and non-critical CAN messages), which reduces the number of CAN messages requiring transmission. In the second stage, the scheduler proposes a Message Scheduling Optimization Algorithm (MSOA) to schedule critical TSN messages. This algorithm reassembles all the critical CAN messages (within the un-schedulable TSN messages) to generate new TSN messages for rescheduling. Experimental results show that our proposed scheduler effectively improves the acceptance ratio of critical and non-critical CAN messages and outperforms the state-of-the-art message scheduling method in terms of acceptance ratio while improving the bandwidth utilization and the number of schedule table entries. We further construct a hardware platform to evaluate the performance of MSOA. The consistency between practical results and theoretical results shows the effectiveness of MSOA.

Final Examination Time Table Scheduling using Integer Programming with Average Time Slot Gap Minimization

Final Examination Time Table Scheduling using Integer Programming with Average Time Slot Gap Minimization

Reuse-based online joint routing and scheduling optimization mechanism in deterministic networks

Deterministic networks plan the entire network traffic and calculate the scheduling time to meet the critical traffic requirements of specific domains, enabling real-time and deterministic interaction of massive data. However, in dynamic industrial automation scenarios where devices undergo changes, existing mechanisms face challenges in quickly responding to dynamic transmission demand changes caused by rapid traffic migration. To address this issue, this paper proposes a reuse-based online scheduling mechanism that utilizes dynamic path planning of flows and coordinated scheduling of time slots to achieve deterministic transmission of dynamic flows. In the offline phase, the mechanism proposes a backbone link selection and a scalable intelligent routing strategy, constructs a set of routing and scheduling co-design constraints, and generates an offline scheduling table using an iterative scheduling algorithm. In the online scheduling phase, a reuse-based online scheduling algorithm is proposed to achieve rapid scheduling and deterministic transmission of dynamic real-time flows. It utilizes the offline scheduling results and the period offset of migrated flows. The reuse of offline scheduling results reduces computation time and expands the solution space. Experimental results demonstrate that the proposed mechanism achieves a maximum increase in scheduling success rate of 37.3% and reduces time costs by up to 66.6% compared to existing online scheduling algorithms.

Research on schedulability analysis algorithm of airborne multi partition system

Partition operating system conforming to ARINC653 is widely used in airborne to support application software integration. Under the two-level scheduling model for partition operating system, the demanding real-time requirements of airborne software are usually difficult to obtain effective deterministic guarantee, so it is very important to analyze the schedulability of the system. Judging whether the scheduling table can meet the real-time requirements of the process in the partition through the schedulability analysis algorithm is an effective means to ensure that all processes in the system complete the computing task within the specified time. Based on the method of operations research and the introduction of virtual process, a schedulability analysis algorithm for multi partition system is designed, and the numerical verification is carried out. The verification results show that the algorithm can accurately judge whether the scheduling table matches the process time attribute, give the qualitative analysis conclusion of whether the system can be scheduled, help the system integrator to verify the rationality of the scheduling table before the actual operation of the system, and reduce the risk of test and flight test.

A Scheduling Method for Heterogeneous Signal Processing Platforms Based on Quantum Genetic Algorithm

Currently, many problems such as variable signal resources, complex execution environments, and low efficiency of scheduling algorithms are faced by heterogeneous signal processing platforms. The task scheduling algorithm is one of the key factors that directly affect the performance of the processing platform. In order to solve the problems of low efficiency of task scheduling algorithms and high computational cost of processors, a heterogeneous platform scheduling algorithm based on the quantum genetic algorithm is proposed in this paper. The algorithm constructs a task scheduling model by using a directed acyclic graph. This paper quantifies the mapping relationship between the quantum genetic algorithm and task scheduling. It corresponds qubits to binary, chromosomes to processor numbers, and individuals to processor scheduling strategies. In this paper, a new way of coding chromosomes using quantum coherence properties is designed to reduce the population size and increase population diversity. Crossover operations are performed on all individuals using full-interference crossover to avoid the results falling into local optimal solutions. The population of slow convergence is solved by implementing mutation operations on populations through quantum rotation gates. In addition, a task pre-ordering stage is designed based on the table scheduling algorithm. The task scheduling priority developed at this stage is used as the reference value for the initial encoding of the population, so that the search space for solutions is reduced. Finally, experiments are conducted using randomly generated task graphs. The algorithm is compared with improved genetic algorithms and existing intelligent scheduling algorithms. The results show that the algorithm can still obtain better results when the number of populations and iterations is small. It is more appropriate for heterogeneous platforms and computation-intensive tasks.

Scheduling for a Container Supply Chain to Minimize Costs Using the Meta-Innovation Approach

In this study, a problem of scheduling shipping lines for a container supply chain is addressed in order to minimize the costs of charging ships and the cost of maintaining the inventory of empty containers in the port by considering the time window of the port and the amount of fuel. This is a hard-NP problem and cannot be solved on a large scale with precise methods in a logical time. Therefore, to solve and optimize the model, a meta-innovative algorithm, a genetic algorithm, has been used. Also, to increase the effectiveness of the genetic algorithm, the parameters of the algorithm are adjusted using the Taguchi method. Finally, a number of problems have been solved to show the performance of this algorithm and its computational results have been compared with the results obtained from GAMS software. The study’s results demonstrate that the efficiency of displacement inside ports and fuel price on the overall costs, the optimal number of ships utilized, and the optimal scheduling table.

Effect of Foreign Exchange Transaction Risk Management on Financial Performance of Firms in Horticulture Industry in Kenya

In Kenya, the horticulture industry is a big revenue earner with the sector earning the country foreign exchange by exporting their products to various countries overseas. However, in the preceding five years to the study, horticultural firms had steadily declined hindering their sustainability and contribution to the economy. The purpose of the study was to determine the effect of foreign exchange transaction risk management on financial performance of firms in horticulture industry in Kenya. To accomplish the objectives, the study employed an explanatory research design to analyse several horticultural enterprises at a certain point in time. Primary data were obtained through a questionnaire that included questions that were both closed and open-ended, while secondary data were acquired using schedule tables. The population of interest for this study was 63 horticultural enterprises in Nakuru County. Due to the study population's small size, a census of all 63 enterprises was done. After collecting data, Statistical package for social sciences (SPSS) version 21 was used to derive descriptive statistics and conduct multiple linear regression analysis. The averages and standard deviation were determined using descriptive statistics, and multiple linear regression analysis was applied to test the study's hypotheses. After that, the output was summarized in reports and frequency tables. The findings revealed transaction risk management having a significance value of 0.000 and a coefficient of 0.533. The significance value of 0.000 was less than the standard 0.05 which implied that foreign exchange transaction risk management had a noteworthy influence on ROCE value at 95 percent confidence level. The study concludes that foreign exchange transaction risk management has an influence on profitability of horticulture firms in Kenya. The study thus recommends that the senior management in the horticultural businesses should enter into a variety of forward contracts and options to enable them to manage this risk effectively and have the expected positive effect on their ROCE. Keywords: Foreign Exchange, Transaction Risk Management, Horticulture Industry, Financial Performance.

Estradiol (E2) levels in premenopausal women with hormone receptor-positive (HR+) breast cancer (BC) on ovarian function suppression (OFS) with gonadotropin-releasing hormone agonists (GnRHa).

524 Background: OFS is an important treatment component for premenopausal women with early and advanced HR+ BC and optimal efficacy may depend on complete E2 suppression with GnRHa, especially when combined with aromatase inhibitors (AI). However, standard assays lack sensitivity and accuracy at very low E2 concentrations, rendering detection of breakthrough ovarian function challenging. More informative data regarding endocrine effects of GnRHa are needed, particularly in young women who derive the most benefit from OFS yet more frequently had breakthrough E2 levels in the SOFT trial substudy, SOFT-EST. Methods: Using a prospective cohort study of women with BC diagnosed at age ≤ 40 years, we identified participants with stage I-IV HR+ BC on OFS treatment with leuprolide, goserelin or triptorelin and blood collected 1 year after diagnosis. Clinical data were obtained through surveys and medical records. Plasma estrogens were measured by liquid chromatography-tandem mass spectrometry, with a limit of detection of 0.2 pg/mL compared to 10 pg/mL with standard assays. We assessed the proportion of women on OFS with E2 > 2.72 pg/mL (10 pmol/L) and > 10 pg/mL. Patient characteristics, estrone (E1) and FSH levels, and disease-free (DFS) and overall survival (OS) were compared between those with and without elevated E2 using Fischer’s exact, Wilcoxon rank sum and log rank tests, respectively. Results: Of 84 patients who met inclusion criteria, 72 (86%) had stage I-III and 12 (14%) had stage IV BC; 25 were on OFS plus AI and 59 were on OFS plus tamoxifen (TAM). Median E2 was 3.1 pg/mL (range 0.2-30.9). 46 patients (55%) had E2 > 2.72 pg/mL, including 8 on AI and 38 on TAM; 4 (5%) had E2 > 10 pg/mL, including 1 on AI and 3 on TAM. Factors associated with E2 > 2.72 pg/mL were no prior chemotherapy, TAM and high E1 ( P ≤.05), but not age, BMI or GnRHa schedule (Table). After a median follow-up of 7 years, DFS events were seen in 6 patients with E2 > 2.72 pg/mL and 5 without ( P =.232); OS events were seen in 7 patients with E2 > 2.72 pg/mL and 5 without ( P =.608). Conclusions: More than half of young women with ER+ BC had E2 > 2.72 pg/mL on OFS, 91% of whom would not have been detected by standard assays. This may be an area amenable to intervention to improve outcomes in young women. However, larger studies are needed to elucidate the optimal E2 target on OFS and clinical implications of incomplete E2 suppression on ultrasensitive assays. [Table: see text]

DATABASE DESIGN FOR PRIVATE HIGH SCHOOL ACADEMIC INFORMATION SYSTEM

This study aims to design a database for a private high school academic information system. This type of research is action research. The development of Information Technology, can support the creation of good management in high school. Information technology is useful so that management in the organization can run and work well. At this time, private high schools do not yet have a database that is able to provide information on student and teacher services, where the database is needed for the academic information system. Therefore, it is necessary to design a database for private high school academic information systems so that the table design is as follows: Student Tables, Teacher Tables, Room Tables, Schedule Tables, Class Tables, Subject Tables, Grades Tables, and Admin Tables and also designed Also the Teacher Login menu, Student Login, Administrator Login, and Student value input menu, Teacher data input menu, Student data input menu, teaching schedule menu, and news management menu. The results of this database design are very useful for private high schools.

Dependability‐aware routing and scheduling for Time‐Sensitive Networking

Time-Sensitive Networking (TSN) extends IEEE 802.1 Ethernet for safety-critical and real-time applications in several areas, for example, automotive, aerospace or industrial automation. However, many of these systems also have stringent security requirements, and security attacks may impair safety. Given a TSN-based distributed architecture, a set of applications with tasks and messages as well as a set of security and redundancy requirements, the authors are interested to synthesise a system configuration such that the real-time, safety and security requirements are upheld. The Timed Efficient Stream Loss-Tolerant Authentication (TESLA) low-resource multicast authentication protocol is used to guarantee the security requirements and redundant disjunct message routes to tolerate link failures. The authors consider that tasks are dispatched using a static cyclic schedule table and that the messages use the time-sensitive traffic class in TSN, which relies on schedule tables (called Gate Control Lists, GCLs) in the network switches. A configuration consists of the schedule tables for tasks as well as the disjoint routes and GCLs for messages. A Constraint Programing-based formulation, which can be used to find an optimal solution with respect to the cost function, is proposed. Additionally, a Simulated Annealing-based metaheuristic, which can find good solution for large test cases, is proposed. The authors evaluate both approaches on several test cases.

Wireless Music Playing Buzzer Sensor-Assisted Music Tone Adaptive Control

Aiming at the problem of adaptive change of auxiliary music tones, this paper proposes a MAC protocol with a common music tone listening/sleeping type based on a wireless music buzzer sensor. First of all, the new MAC protocol adopts network-wide synchronization, and all sensor nodes in the entire network use the same scheduling table, so that the entire network nodes enter the music tone listening period and the sleep period at the same time. Secondly, the node adaptively adjusts the duty cycle of the node according to the number of data packets in the sending queue, increases the node’s music tone listening time, reduces the end-to-end delay of data packets, and improves the throughput of the network. Then, the experiment adopts a new backoff strategy to adjust the contention window according to the backoff times and collision times of data packets sent by nodes in the last five working cycles, increase the backoff time of sending data packets under high network load, and reduce the appearance of data packets. We build four simulation experiments on the NS2 simulation platform: unassisted music tone adaptive network, single auxiliary music tone adaptive network, auxiliary music tone adaptive convergence network, and random deployment network, which will be based on the auxiliary music tone adaptive MAC protocol, and IEEE802.11 protocol and SMAC protocol are run in four simulation experiments, respectively, and the performance of the three protocols is analyzed according to the tracking files in the simulation experiment. The analysis results show that the simulation wireless sounding buzzer sensor network is adaptive to different auxiliary music tones and different topologies.

Configuring ADAS Platforms for Automotive Applications Using Metaheuristics.

Modern Advanced Driver-Assistance Systems (ADAS) combine critical real-time and non-critical best-effort tasks and messages onto an integrated multi-core multi-SoC hardware platform. The real-time safety-critical software tasks have complex interdependencies in the form of end-to-end latency chains featuring, e.g., sensing, processing/sensor fusion, and actuating. The underlying real-time operating systems running on top of the multi-core platform use static cyclic scheduling for the software tasks, while the communication backbone is either realized through PCIe or Time-Sensitive Networking (TSN). In this paper, we address the problem of configuring ADAS platforms for automotive applications, which means deciding the mapping of tasks to processing cores and the scheduling of tasks and messages. Time-critical messages are transmitted in a scheduled manner via the timed-gate mechanism described in IEEE 802.1Qbv according to the pre-computed Gate Control List (GCL) schedule. We study the computation of the assignment of tasks to the available platform CPUs/cores, the static schedule tables for the real-time tasks, as well as the GCLs, such that task and message deadlines, as well as end-to-end task chain latencies, are satisfied. This is an intractable combinatorial optimization problem. As the ADAS platforms and applications become increasingly complex, such problems cannot be optimally solved and require problem-specific heuristics or metaheuristics to determine good quality feasible solutions in a reasonable time. We propose two metaheuristic solutions, a Genetic Algorithm (GA) and one based on Simulated Annealing (SA), both creating static schedule tables for tasks by simulating Earliest Deadline First (EDF) dispatching with different task deadlines and offsets. Furthermore, we use a List Scheduling-based heuristic to create the GCLs in platforms featuring a TSN backbone. We evaluate the proposed solution with real-world and synthetic test cases scaled to fit the future requirements of ADAS systems. The results show that our heuristic strategy can find correct solutions that meet the complex timing and dependency constraints at a higher rate than the related work approaches, i.e., the jitter constraints are satisfied in over 6 times more cases, and the task chain constraints are satisfied in 41% more cases on average. Our method scales well with the growing trend of ADAS platforms.

An algorithm to build schedule table for schedule-based fieldbus to reduce communication jitter to its minimum

Schedule-based fieldbus is applied widely in industrial control. Building schedule table (ST) can affect the time-critical performance for communication greatly. Communication jitters can cause some unexpected results in bus traffic scheduling and longer jitters can even cause severe delay in time-critical application. Communication jitter and evenness in arrangement of variables to be scheduled in micro-cycles in ST were two important issues dealing with the performance. An algorithm to build schedule table based on numerical co-prime method was proposed in this paper. Communication jitter in ST was investigated. Concept dealing with rank of ST was introduced. Numerical co-prime method to evaluate rank of ST was proposed. The algorithm and procedure to build schedule table based on the proposed numerical co-prime method were presented and exemplified in detail. Performance analysis and comparison of the proposed algorithm to HCF/LCM method was presented. It was proved that the proposed algorithm can reduce communication jitter to its minimum value and the longest time consumed to schedule variable in one micro-cycle, and greatly reduce the possibility the time consumed to schedule variables exceeded micro-cycle.

Heuristic fragmentation-aware scheduling for a multicluster time-sensitive passive optical LAN

With the development of Industry 4.0, optical networks are playing a key role in carrying large amounts of data traffic in industrial networks. Multicluster time-sensitive passive optical local area networks (POLs) use passive optical networks (PONs), which are important optical network segments, as local area networks (LANs); such networks can provide high-capacity real-time communications for large-scale industrial systems and have the potential to replace legacy LANs in industrial networks. To satisfy dynamic application requirements, POLs for future industrial networks need to be sufficiently flexible to adapt to frequent changes. Hence, this paper proposes a heuristic fragmentation-aware scheduling (FAS) method based on fast list scheduling for the scheduling of real-time traffic in multicluster time-sensitive POLs. The FAS algorithm selects a scheduling plan in accordance with a fragmentation calculation, schedules one time-triggered (TT) flow at a time from the pending scheduled TT flow set, and incrementally updates the scheduling table. The list processing mechanism of list scheduling is modified to improve scheduling performance, while the fast speed of list scheduling is inherited. Simulation results show that compared with a basic rate monotonic scheduling (RMS) list scheduler, FAS significantly increases the schedulable scale and schedulable load of the TT flow set while markedly reducing the TT communication overhead. With the help of FAS, multicluster time-sensitive POLs can support more critical tasks with higher network efficiency, allowing them to better cope with future dynamic and complex industrial application scenarios.

Time-predictable routing algorithm for Time-Sensitive Networking: Schedulable guarantee of Time-Triggered streams

To make manufacturers more intelligent in the production of cyber-physical systems (CPS), the IEEE 802.1 working group proposes a Time-Sensitive Network (TSN) standard based on traditional Ethernet. TSN can help the industrial environment to realize intelligent real-time transmission requirements. At present, the research on TSN focuses mainly on how to optimize the scheduling table synthesis to reduce the end-to-end delay of the frame. Routing selection typically uses the common shortest path first (SPF) and weighted shortest path first (wtSPF) algorithms. The path chosen by these algorithms can only ensure a low end-to-end delay of newly added streams, but they cannot guarantee the success rate of scheduling newly added streams or determine whether the delay will have a serious impact on other streams. Therefore, this paper proposes a scheduling routing algorithm for the TSN environment, named Real-Time Routing Scheduler (RTRS), which is applicable to Time-Triggered (TT) streams with immediate constraints. Based on the calculation of the end-to-end maximum delay time, the RTRS is used as a basis for routing to ensure that all TT streams are transmitted within the deadline. The experimental results show that the RTRS algorithm can provide an excellent real-time performance of CPS, improve the scheduling success rate, optimize the maximum end-to-end delay, and ensure that newly added streams do not easily affect the transmission of other streams.

A Cost-Effectiveness Analysis of Neuraminidase Inhibitors for Influenza Virus Infections in an Adult-Outpatient Setting in Japan

BackgroundPharmacoeconomic studies have been less performed in Japan. The objective of this study was to clarify which neuraminidase inhibitor (NI; oseltamivir, zanamivir, laninamivir, and peramivir) is most cost-effective in an adult outpatient setting in Japan. ObjectiveTo clarify which neuraminidase inhibitor (NI; oseltamivir, zanamivir, laninamivir, and peramivir) is most cost-effective in an adult outpatient setting in Japan. MethodsCost-effectiveness analysis was constructed from the healthcare payer’s perspective. A decision tree model was constructed with probabilities from relevant randomized controlled trials. Costs included medical costs and drug prices. Medical costs were obtained from the medical fee schedule table (2016 version). We also applied authorized medication costs. Outcomes of effectiveness were measured using EQ-5D-3L questionnaires for adult patients who had experienced influenza virus infections previously. Time horizon was 14 days in this study. ResultsCost-effectiveness ratios for oseltamivir, zanamivir, laninamivir, and peramivir were 393 674 Yen/quality-adjusted life year (QALY; US$3883.41/QALY), 408 241 (US$4027.10), 407 980 (US$4024.53), and 444 264 (US$4382.45), respectively. The cost-effectiveness analysis base-case analysis revealed oseltamivir as the most cost-effective NI. Zanamivir was dominated. Incremental cost effectiveness ratio (ICER) for laninamivir and peramivir were 1 129 459 Yen/QALY (US$11 141.58/QALY) and 1 287 118 (US$12 696.81), respectively. One-way sensitivity analyses revealed that minimum ICERs for laninamivir based on “quality of life (QOL) values (95% confidence interval)” was −596 850 Yen/QALY (US−$5887.64/QALY) owing to high cost and less effective. Also, maximum ICER for peramivir based on“QOL values” was 14 717 518 Yen/QALY (US$145 181.32/QALY); a value more than the 5 000 000 Yen/QALY threshold. ConclusionsThe study results reveal oseltamivir as the most cost-effective NI for the treatment of influenza virus infection in an adult outpatient setting. Our findings may provide decision makers with scientific evidence for clinical and economic evaluation to achieve optimal therapeutic outcomes.