Service Scheduling Research Articles

Reschedule the Shunting and Service Scheduling Plan After Disturbances at a Chinese High-Speed Railway Depot

Reschedule the Shunting and Service Scheduling Plan After Disturbances at a Chinese High-Speed Railway Depot

Space ‘Tourism’: a Framework for Ensuring ‘Safe and Orderly Development’ Lessons Learnt from the U.S. and Aviation

In August 2023, following its successful mission, Virgin Galactic announced the intention to provide scheduled services into space. Yet, this paper sets out to present evidence to argue that, from an international (U.N.) perspective, there has been a lack of activity to establish safeguards and to ensure a fit for purpose governance and oversight mechanism is in place for this new and growing sector—space tourism. The research is undertaken by way of a comparison law/policy analysis which factors in key historic events across both aviation and space. The main focus is given to the developments and approach of the U.S. The research finds that there remains a number of areas where clarity and advancement is needed both nationally (U.S.) and internationally; and that, without suitable governance and frameworks being established—safety is compromised, and equitability is not ensured for space tourists. It is advocated that there are clear lessons to be learnt from aviation developments and practices and that one solution would be a governance and oversight system as has been established by the International Civil Aviation Organization (ICAO).

Digital Twin of a battery-based EV charging station to support services

Digital Twin (DT) concepts and applications have been evolving to explore the potential to support Product-Service Systems (PSS). At the same time, DT newest developments include Electric Vehicle’ (EV) battery systems. However, the literature on Digital Twins of EV charging stations as service systems is still limited. This work presents a Digital Twin information architecture of an EV charging station aiming to support the related services. The proposed information architecture has been applied to a novel battery-based EV mobile charging platform under development. The prototyped application utilizes battery charge and discharge data to enable a scheduling service. Other services, such as reservation, SoX estimation, and lifecycle management, are also discussed. Results contribute to the expanding literature on the relationship between DT and PSS, focusing on mobility electrification. Such a service-oriented perspective of the Digital Twin application has the potential to foster innovative business models and highlight value for stakeholders.

A digital twin-based decision support approach for AGV scheduling

The dynamic and complex environment affects the operational efficiency of automated guided vehicles (AGVs) at automated container terminals, in which artificial intelligent approaches are applied to address optimization problems in dynamic systems. This paper proposes a digital twin-based decision support approach to improve the efficiency of AGV scheduling service. Accordingly, the factors that affect AGV scheduling performance, including conflicts, failures, and battery constraints, are discussed first. Then, the framework and main steps of the proposed approach are described. The physical operation space is mapped into the virtual space, and both spaces keep synchronized to support the verification of solutions. A mathematical programming model and Q-learning algorithm are used to generate the AGV scheduling plan considering battery charging. Numerical experiments are conducted to demonstrate the effectiveness of the proposed approach. Comparisons of the digital twin-based approach, genetic algorithm (GA), and particle swarm optimization (PSO) are also made with different scale experiments. It appears that the proposed digital twin-based approach is superior to GA and PSO when solving small- and large-scale cases. A sensitivity analysis is performed concerning the battery utilization rate, task, and AGV number. Experimental results show that an optimal configuration of AGV and task can improve the battery utilization rate and reduce the completion time.

PELAKSANAAN BIMBINGAN ROHANI ISLAM DALAM MENGELOLA EMOSIONAL PASIEN DI RUMAH SAKIT ISLAM METRO

Islamic spiritual guidance services in fostering the emotional state of internal medicine patients at the Metro Islamic Hospital are motivated by the many problems in the emotional condition of internal medicine patients such as boredom, sadness, disappointment, stress and lack of confidence. The problem in this study is that patients at the Metro Islam Hospital who are given spiritual guidance by counselors experience emotional instability due to their physical condition. The purpose of this study is to explain the implementation of Islamic spiritual guidance services in fostering emotional internal medicine patients at Metro Islam Hospital. This type of research is, field research (Field Research). While the nature of the research is descriptive. The location of this research is Metro Islam Hospital. Data collection techniques used are interviews, observation, and documentation. This study uses the Miles and Huberman model to analyze the research data.
 The results showed that in the implementation of Islamic spiritual guidance for internal medicine patients at the Metro Islam Hospital there is a service schedule that is carried out every Monday to Friday. The methods used in Islamic spiritual guidance are the direct guidance method and the indirect guidance method. The forms of Islamic Spiritual Guidance Services that are carried out are a) guidance services consisting of tadzkirah guidance, worship guidance, dhikr and prayer guidance, guidance for patients with special needs, and funeral relocations; b) Spiritual consultation services, this service is more focused on patients who experience spiritual problems that can interfere with their psychology; c) Spiritual development services. There are three stages in carrying it out, namely the pre-service stage, the process stage and the post-service stage.

A new measure of node centrality on schedule-based space-time networks for the designation of spread potential

Node centrality is one of the most frequently revisited network theoretical concepts, which got many calculation method alternatives, each of them being conceived on different empirical or theoretical network abstractions. The vast majority of centrality measures produced up to date were conceived on static network abstractions (the so-called “snapshot” networks), which arguably are less realistic than dynamic (temporal) network abstractions. The new, temporal node centrality measure that we offer with this article, is based on an uncommon abstraction, of a space-time network derived from service schedules (timetables). The proposed measure was designed to rank nodes of a space-time network based on their spread or transmission potential, and was subsequently implemented on the network of sea ferry transportation derived from the aggregated schedules for sea ferry liner shipping services in Europe, as they occurred in the month of August, 2015. The main feature of our measure, named “the Spread Potential”, is the evaluation of the potential of a node in the network for transmitting disease, information (e.g. rumours or false news), as well as other phenomena, whichever support a space-time network abstraction from regular and scheduled services with some known carrying capacities. Such abstractions are, for instance, of the transportation networks (e.g. of airline or maritime shipping or the wider logistics (delivery) networks), networks of medical (hospital) services, educational (teaching) services, and virtually, of any other scheduled networked phenomenon. The article also offers the perspectives of the measure’s applicability on the non-scheduled space-time network abstractions.

Will air taxis extend public transportation? A scenario-based approach on user acceptance in different urban settings

Increasing urbanization has led to rising mobility and infrastructural challenges for cities and surrounding areas. Electrical vertical takeoff and landing aircrafts, also known as air taxis, enable the use of a new dimension, the skyscape. Air taxis provide a local, emission-free transport option and an infrastructure-conserving solution for the public transportation sector. While the technical implementation has already proved itself, user awareness is not yet widespread. Additionally, essential feasibility factors for public use, such as price, have received scant attention. Since user acceptance is necessary for successful implementation, and willingness to pay is another important indicator for future infrastructure planning, this study aims to investigate different urban transport scenarios. Within the framework of the study, societal acceptance, individual intention to use, and willingness to pay were investigated. Data collection took place in the greater Dresden area in Germany, with a final sample of 1,074 participants. The resulting data suggest an overall limited intention to use and societal acceptance. The scenario analysis revealed a “limousine-like” dial-a-ride scenario as a potential successful path to follow, in which a transitional path with initial dial-a-ride services and growing scheduled services over time is regarded as the most probable. Consumers’ willingness to pay was highest for the limousine scenario. Based on this research, governmental authorities and industry stakeholders may consider the findings to develop a human-centered approach for future mobility and ensure successful implementation in the mobility networks of the future.

Enterprise and service−level scheduling of robot production services in cloud manufacturing with deep reinforcement learning

Enterprise and service−level scheduling of robot production services in cloud manufacturing with deep reinforcement learning

Fairness model considering satisfaction and preferences for service scheduling on electronic platforms in construction industry

Advancements of electronic platforms in construction industry makes it possible for construction service scheduling (CSS). However, fairness concerns in CSS, such as unfairness in scheduling solutions due to information asymmetry, remains inadequately addressed among existing studies. This study proposes a fairness scheduling model that considers the preferences of participants. According to real engineering practices, a multi-level CSS model with 12 objectives is established by thoroughly considering participants’ preferences, aiming to deliver equitable prices and CSS solutions. In solving the model, a clustering operation considering price fairness and inheritance operation considering participants’ preferences are designed for the developed evolutionary algorithm. Finally, a simulated case study derived from a real-world construction project demonstrates the effectiveness of the proposed model and algorithm. The results show the superior performance of the proposed model, as it recommends fairer prices and solutions to the CSS problem over the five comparator models. Meanwhile, the proposed algorithm offers more fair solutions with better comprehensive performance than the NSGA3, MOEA/D, MOEA/DD, and RVEA algorithms. This study can be extended to scheduling fairness issues in other fields (e.g., e-commerce, cloud manufacturing, and energy trading), while providing references for researches on service scheduling.

A Systematic Review on Various Task Scheduling Algorithms in Cloud Computing

Task scheduling in cloud computing involves allocating tasks to virtual machines based on factors such as node availability, processing power, memory, and network connectivity. In task scheduling, we have various scheduling algorithms that are nature-inspired, bio-inspired, and metaheuristic, but we still have latency issues because it is an NP-hard problem. This paper reviews the existing task scheduling algorithms modelled by metaheuristics, nature-inspired algorithms, and machine learning, which address various scheduling parameters like cost, response time, energy consumption, quality of services, execution time, resource utilization, makespan, and throughput, but do not address parameters like trust or fault tolerance. Trust and fault tolerance have an impact on task scheduling; trust is necessary for tasks and assigning responsibility to systems, while fault tolerance ensures that the system can continue to operate even when failures occur. A balance of trust and fault tolerance gives a quality of service and efficient task scheduling; therefore, this paper has analysed parameters like trust and fault tolerance and given research directions.

Adaptive scheduling of mixed bus services with flexible fleet size assignment under demand uncertainty

This paper presents an optimization framework for adaptive scheduling of mixed bus services with flexible fleet size assignment under demand uncertainty. The service scheduling plans are driven by prevailing stochastic passenger demand subject to operational constraints. The optimization problem is formulated as a Markov decision process which aims to minimize passengers’ in-vehicle and waiting times, as well as the operator’s cost via use of services with different routes, schedules, and fleet sizes. To address the computational challenges, the solutions to the problem are to be calculated with use of reinforcement learning techniques. The proposed framework is implemented and tested using real-world scenarios configured from actual bus service route in Hong Kong. Experiment results reveals the benefits of the proposed bus service scheduling framework with use of flexible routes and fleet sizes in saving passengers’ and operator’s costs. This study contributes to real time transit operational planning with advanced computing and optimization techniques.

IDENTIFIKASI, EVALUASI DAN REKOMENDASI LAYANAN LUMPUR TINJA DI KOTA BANJARBARU KALIMANTAN SELATAN

The feces waste treatment installation (IPLT) pond capacity of Banjarbaru is 20 M3/ day, while the maximum amount per month in 2022 is only 11 M3 of household fecal waste that goes into IPLT. This shows that the excrement that enters the IPLT is below the IPLT capacity of Banjarbaru because currently, the sludge service has yet to be scheduled and is still using the on-call system. Meanwhile, Banjarbaru Regional Regulation No. 1 of 2021 regarding scheduled sludge services in Banjarbaru already exists. This study aims to identify and evaluate the existing conditions of the sludge service in Banjarbaru and develop recommendations for improving the sludge service in Banjarbaru. The method used in this research is a descriptive method using a questionnaire and conducting interviews with people who have used sludge services in 2022. Calculation of the results of the questionnaire uses a Likert scale, validity, and reliability tests. The results of the identification through the questionnaire revealed that the IPLT had been actively carried out with the on-call system; if implementing the scheduled feces sludge service (LLTT), several processes had to be improved, and the results of the evaluation stated that the community did not agree with the fees charged for the LLTT. Recommendations for sludge services are increasing the number of fleets, promoting sludge services, and improving the administration system.

Equitable Care for Severe Hemophilia_A: Distributional Cost-Effectiveness of Prophylactic Weekly Efanesoctocog Alfa Versus Standard-Care Factor VIII in Patients with Severe Hemophilia_A in the United States

Introduction: Prophylactic coagulation factor replacement is crucial to decrease bleeding episodes and improve quality-adjusted life expectancy (QALE) for patients with severe hemophilia A. Even with prophylactic treatment (i.e., at three to four times weekly) patients remain at risk of bleeding events and still develop chronic arthropathy across their lifetimes. The additional economic burden associated with lifelong prophylactic treatment is a major equity concern for patients with hemophilia A and their families. Efanesoctocog alfa is a recently developed extended half-life agent for hemophilia A prophylaxis and management, supporting the possibility of once-weekly prophylaxis. An open-label multicenter study (XTEND-1) showed that once-weekly dosing of efanesoctocog alfa improves the annualized bleeding rate (ABR) by 77% versus prophylaxis with standard-care factor VIII in patients with severe hemophilia A. We sought to evaluate, both for the first time, the conventional and distributional cost-effectiveness of prophylaxis with efanesoctocog alfa versus with standard-care factor VIII for patients with severe hemophilia A in the United States. Methods: For this independent analysis free of industry influence, we built a Markov model to examine the conventional cost-effectiveness of prophylaxis with efanesoctocog alfa versus standard-care factor VIII for patients with severe hemophilia A. Transition probabilities for ABRs and product utilization were informed by phase 3 study data and supplemented with FDA package insert information. Within ABRs, we accounted for treated bleeding severity and bleeding event types, inclusive of hemarthrosis, intracranial hemorrhage, in addition to assuming the prevalence of chronic arthropathy with SHL (i.e., due to silent bleed burden) is eliminated by efanesoctocog alfa. Costs for the base-case were sourced from the Centers for Medicare & Medicaid Services with negotiated (i.e., lower) cost of efanesoctocog alfa supplied from the Veterans Affairs Federal Supply Schedule Service (VA-FSS). Age-, sex- and disease-specific background mortality were employed. Utilities for severe hemophilia A and disutilities for bleed events and hospitalizations were informed by extensive literature specific to severe hemophilia A. The primary outcome was the incremental cost-effectiveness ratio (ICER) in USD/QALY, at a willingness-to-pay threshold of $150,000/quality-adjusted life-year (QALY). The secondary outcome was a threshold analysis for the maximum efanesoctocog alfa price that renders efanesoctocog alfa prophylaxis cost-effective. To account for health inequities in the care of patients with hemophilia A we then conducted a distributional cost-effectiveness analysis (DCEA) to derive an equity weight threshold (i.e., inequality aversion parameter) for the decision of prophylaxis with efanesoctocog alfa versus with standard-care factor VIII. This threshold was then compared to prior estimates for commonly used equity weights in the United States (range 0.5-3.0). Results: In the base-case, prophylaxis with efanesoctocog alfa versus with standard-care factor VIII accrued 19.4 and 15.4 QALYs at mean costs of $17.3 and $9.7 million. The ICER for efanesoctocog alfa was $1,890,000/QALY (95% credible interval 1,190,000-3,330,000). Threshold analysis showed that prophylaxis with efanesoctocog alfa became cost-effective when the price of efanesoctocog alfa decreased by at least 59%. In deterministic sensitivity analysis, the model was most sensitive to the costs of efanesoctocog alfa and factor VIII. In probabilistic sensitivity analysis, standard-care factor VIII was favored over efanesoctocog alfa in 100% of 10,000 Monte Carlo simulations. The equity weight threshold for the treatment decision of prophylaxis with efanesoctocotog alfa versus with standard-care factor VIII was 7.4, higher than commonly used equity weights in the US. This implies a threshold that is higher than what has previously been used in the United States, per DCEA standards. Conclusion: As compared to standard-care factor VIII and at VA-FSS pricing, efanesoctocog alfa prophylaxis is conventionally cost-ineffective for patients with severe hemophilia A. Prophylaxis with efanesoctocog alfa does not meet commonly used distributive equity standards in the United States at this time.

PENENTUAN OBJEK WISATA FAVORIT DI PULAU NUSA PENIDA MENGGUNAKAN SIMPLE ADDITIVE WEIGHTING METHODE (SAW)

The level of development of tourism in Klungkung especially in Nusa Penida has experienced a significant increase. This is inseparable from the smooth sea transportation in the form of speedboats with additional service schedules. The increase has also been influenced by the discovery of a number of new tourist attractions and maritime tours that are especially enjoyed by foreign tourists (diving and snorkeling). The location of the tourist attractions are not in one place but spread in several places with a considerable distance. If the vacation is only for one day, then the tourists must be able to choose attractions that line between the departing lane and the return lane so that it is more efficient. The data to be used in this study are internal and external data, alternatives that will be compared are a number of tourist sites with several criteria to be used. The method for processing data to be used is one of the methods in the Multi-Attribute Decision Making (MADM), the Simple Additive Weighting (SAW) Method. This method is used to find weighted sums and performance ratings on each alternative on all attributes. Research methods carried out starting from literature studies, interviews, data analysis to be used, data processing with the method of Simple Additive Weighting (SAW) method. The research is done in order to enable the tourists to determine the choice of tourist attractions that will be visited during their vacation on the island of Nusa Penida more easily. Based on the criteria and alternatives used, the study has resulted in having Cystal Bay as the most visited tourist attraction with a total preference value of 2.9200.

Artificial Intelligence-Based Chatbots to Combat COVID-19 Pandemic: A Scoping Review

Context: Artificial intelligence (AI) Chatbots are computer programs that simulate human conversation and use artificial intelligence, including machine learning and natural language processing, to interact with users via natural language. With the outbreak of the COVID-19 pandemic, the use of digital health technologies such as chatbots has accelerated. Objectives: This study aims to investigate the application of AI chatbots in combating the COVID-19 pandemic and explore their features. Methods: We reviewed the literature on health chatbots during the COVID-19 pandemic. PubMed, Scopus, Web of Science, and Google Scholar were searched using relevant keywords such as “chatbot”, “conversational agent,” and “artificial intelligence”. To select the relevant articles, we conducted title, abstract, and full-text screening based on inclusion and exclusion criteria. Chatbots, their applications, and design features were extracted from the selected articles. Results: Out of 673 articles initially identified, 17 articles were eligible for inclusion. We categorized the selected AI chatbots based on their roles, applications, and design characteristics. Around 70% of chatbots were designed to play a preventive role. Our review identified 8 key applications of the AI chatbots during the COVID-19 pandemic, which include (1) information dissemination and education, (2) self-assessment and screening, (3) connecting to health centers, (4) combating misinformation and fake news, (5) patient tracking and service delivery (6) mental health (7) monitoring exposure (8) vaccine information and scheduling. AI chatbots were deployed on various platforms, including mobile apps, web, and social media. Mobile-based chatbots were the most frequent. All chatbots used Natural Language Understanding (NLU) methods to understand natural language input and act on the user’s request. More than 50% of AI chatbots used NLU platforms, including Google Dialogflow, Rasa framework, and IBM Watson. Conclusions: AI chatbots can play an effective role in combating the COVID-19 pandemic. Increasing people’s awareness, optimizing the use of health resources, and reducing unnecessary encounters are some of the advantages of using AI chatbots during the COVID-19 outbreak. Using NLU platforms can be a suitable solution for developing AI chatbots in the healthcare domain. With advancements in the field of artificial intelligence, it seems that AI chatbots will have a promising future in healthcare, particularly in public health, chronic disease management, and mental health.

A real-time synchromodal framework with co-planning for routing of containers and vehicles

This paper considers a decentralized container transport system in which two decision-makers are involved in getting a container from its origin to its destination: a logistics service provider (LSP) and a flexible service operator (FSO). While the LSP receives shipment requests from shippers and controls the movement of containers over a multimodal network by booking scheduled (e.g., barges and trains) and flexible services (e.g., trucks) from service operators, the FSO manages a fleet of vehicles (e.g., trucks) that have flexible routes and departure times to fulfill the transport requests proposed by the LSP. In the literature, most of the studies focus on either container routing, by assuming all services have fixed routes and trucks are unlimited, or vehicle routing in a road network. This paper investigates the integrated problems of routing containers and vehicles through a multimodal network from a decentralized perspective considering the decision authorities of the LSP and the FSO. A synchromodal framework is designed to control the decision process which enables to utilize the benefits of real-time mode and route changes. To investigate the impact of communication, we develop a co-planning method under the synchromodal framework to coordinate the transport plans between the LSP and the FSO in real-time. The co-planning method considers a realistic level of information exchange and adheres to no changes in their responsibilities and authorities compared to current practice. The performance of the co-planning method is evaluated under various scenarios. The experimental results show that co-planning, using expected transport request fulfillment as feedback, reduces the total costs of container transportation and decreases the distance traveled by flexible vehicles under most of the scenarios.

Evaluasi Program Pelayanan Administrasi Kependudukan Siap Melayani Identitas Dan Pencatatan Sipil Di Kabupaten Buleleng

ABSTRACT
 Public services are an important aspect of the government system, because the government is basically a servant of the community. Population Administration Services are one of the basics of the public service system, however, the problem of heterogeneous conditions causes problems for the community in population administration services. Therefore, DISDUKCAPIL Buleleng Regency implemented the SIMELIK program with a pick-up and drop-off system in population administration services. This research was conducted in 8 sub-districts in Buleleng Regency. The informants for this research consisted of 1) Head of SIMELIK's population administration and civil registration services in Buleleng Regency; 2) Head of population registration services; 3) Coordinator of SIMELIK population administration services; 4) the target community for the SIMELIK program. Data collection techniques were carried out by conducting interviews and observations. The data analysis technique used was qualitative descriptive analysis. The results of this research show that the program implementation has been running effectively and efficiently because it has been able to increase service targets to the community. The community can be reached more widely and more evenly through scheduled services. However, there are obstacles in implementing the program where the socialization carried out does not reach a wide range so that most people do not know about the program being implemented. Another obstacle is that the equipment used is classified as old, so it is necessary to rejuvenate the equipment used to provide services. Another obstacle is the lack of energy used so that it has not been able to reach a wider and optimal reach.

Container Power Consumption Prediction Based on GBRT-PL for Edge Servers in Smart City

Edge computing and IoT devices have been widely deployed in smart city applications due to the rapid promotion and implementation of 5G communication technology. Limited by power supply and hardware computing capability, applications on edge servers are mostly deployed and run in the form of container micro-services to improve resource utilization. Therefore, identifying the power consumption at the container granularity is of great importance for the load scheduling and service quality assurance of edge servers. In this paper, a GBRT-PL-based container power prediction method is proposed. Performance metrics with a strong correlation between container and server power consumption are selected for power consumption modeling. To effectively suit the nonlinear relationship between container performance metrics and server power consumption, the integrated predictive capabilities of multiple regression trees and the segmented linear model of single regression tree leaf nodes are applied. The data from the experiments prove that the GBRT-PL model predicts power consumption more accurately than other models for single and multiple container groups. The highest average relative error rate in the four multi-container group tests is 6.72%, whereas the highest relative error rate in the 90% quantile is 11.66%. In addition, it can accurately predict the majority of power consumption peaks, which contributes to the precise detection of power consumption anomalies.

IFogger: A New Framework to Simulate Fog Computing Resource Placement inside OMNeT++ Environment

The capabilities of the cloud are extended to intermediate network devices by fog computing, providing computational and storage resources. This extension enables the execution of applications closer to edge devices and end-users by deploying services on these intermediate devices. The performance of the fog architecture is significantly impacted by the placement of these services. In this study, iFogger, a fog computing simulator, is proposed to analyze the design and deployment of applications using customized and dynamic strategies. To achieve this, the relationships among deployed applications, network connections, and infrastructure characteristics are modeled using complex network theory. This allows the integration of topological measures in dynamic and customizable strategies, including the placement of application modules, workload location, and path routing and scheduling of services. The iFogger simulator is built on top of the OMNeT++ network simulator. A comparative analysis is performed to assess the efficiency and convergence of results obtained with our simulator compared to the widely referenced iFogSim. The results show that iFogger exhibits better performance in terms of simulation time convergence.

Artificial Intelligence-Based Chatbot to Support Public Health Services in Indonesia

The aim of this study is to build an artificial intelligence chatbot application to support public health services. The chatbot acts as an information service that can replace the role of humans. The analysis of functional needs was obtained from information submitted by one of the heads of public health centers in Indonesia. This study uses the Scrum method with pregame stages to produce a plan consisting of functional and non-functional requirements analysis and conceptual design of the chatbot, which will be developed using Unified Modeling Language (UML) diagrams. The process of finding answers uses the matching graph master technique, which is a backtrack matching that utilizes a depth-first search strategy. There are 6 topics of chatbot services, including service schedules, health information, registration, diseases, drugs, and early care services for chatbot users. Tests conducted on these 6 topics showed an average correct answer ratio of 93.1% out of a total of 251 questions. The result of the usability measurement on the chatbot application that has been built obtained a system usability scale value of 80.1, indicating that the developed chatbots are acceptable for use.