Schedule Coordination Research Articles

Design of a Web-Based Lecture Scheduling Information System During Pandemic Covid-19 (Case Study: Faculty of Engineering and Science, Ibn Khaldun University)

During the Covid-19 pandemic, the lecture process was carried out online, so it impacted other academic activities such as the preparation of lecture schedules. The results of observations at the Faculty of Engineering and Science found that the practice of lecture schedules was carried out manually, such as the schedule coordination process was carried out face-to-face between study programs, faculties, and lecturers to overcome conflicts in the use of rooms and teaching time. Changes in the teaching schedule need to be re-checked on the use of the room and the lecturer's teaching time because it has not been documented with the information system. Hence, this study aims to build an information system for preparing lecture schedules using the Greedy Best First Search Method based on the willingness of lecturers to teach. The system was developed using the RAD (Rapid Application Development) and testing using BlackBox testing. The results of this study succeeded in building a lecture scheduling information system that was able to generate lecture schedules automatically and quickly without having to coordinate face-to-face to support online lectures during the Covid-19 pandemic.

Scheduling coordination of back pressure CHP coupled electricity-heat energy system with adaptive constraint strategy to accommodate uncertain wind power

A scheduling coordination approach with adaptive constraint strategy is proposed for electricity-heat integrated energy system (IES). The approach takes full advantage of heat network flexibility to smooth uncertain wind power and its natural storage capability to improve operational economics. Transmission dynamics of heating network is modeled by describing the heat dissipation in radial direction toward the insulation layer and the heat propagation in axial direction through water flow. Dynamical heating flow and steady power flow with different timescales are integrated to constitute the coordinated scheduling optimization by energy coupling component, i.e. CHP (combined heat and power) unit. In order to mitigate the discrepancy between the predicted and real values of wind power by utilizing the allowed upper limit of water temperature constraint violation, a PID idea based closed-loop adaptive adjustment strategy is implemented on the water temperature constraint at the beginning of supply pipeline. Simulations are conducted to show that in the proposed coordinated scheduling approach, heat network can serve as a natural energy storage to achieve the economic operation of IES, and simultaneously wind power uncertainties can be smoothed by the flexible temperature constraint of water flowing in heat network, with no any probability distribution information of uncertainties needed.

Organizational and economic mechanism of the automatic underground train operation system

This work deals with the provision of underground, as one of the main modes of public transport, with automated control systems, in particular the provision of automated train management. It defines that the underground is one of the most progressive modes of transport, which is related to its environmental safety, comfort, and speed of movement, as this mode of transport does not intersect with other transport and pedestrian routes, which excludes traffic blocks. Underground is an important element of urbanized spaces, for it serves large passenger traffic. The article presents an algorithm for the creation of an automated control system for the underground train system. Based on this algorithm, a model of building an organizational and economic mechanism for automation of control systems has been developed. The diagram of organizational and technical implementation of the automated system of underground train management is presented. An economic analysis of the effectiveness of the application of the automated control system of underground trains was carried out. The recoupment on the acquisition and installation of automation systems is very high. The application of the automated system will increase the capacity of the underground by optimizing the traffic schedules, which will contribute to increasing its profitability. It is also useful to determine the reduction of electricity consumption due to the change in the dynamics of acceleration and braking systems, which is important, as the underground is a powerful enterprise. In the future, a promising direction is to streamline the coordination of train schedules and other modes of land public transport.

Real-time Coordinated Scheduling for Cloud Radio Access Networks in a Software-only Environment using the OpenAirInterface Platform

The objective of this paper is to extend into the OpenAirInterface platform the Coordinated Scheduling (CS) technique to allocate resource blocks among User Equipment (UE) in a wisely way and to control the energy efficiency, the throughput, and the inter-cell interference for Cloud Radio Access Networks (C-RANs). It is achieved by modifying the OpenAirInterface scheduler code, increasing the Remote Radio Unit (RRU) scalability, and employing some component carriers of the Radio Cloud Center (RCC), each one them with one or more UEs. The hardware utilized is composed of general-purpose processors and fast Ethernet transport ports, and the software is recent frequency-domain methodologies in a software-only environment where the use of radio units are not required. However, the USRP B200 mini-i radio unit and the UE (Samsung Galaxy S8) were considered only for validation purposes. The emulations using frequency-domain methodologies, compatible with fourth and fifth-generation cellular systems, allowed real-time emulations and reduced 10-fold the multipath channel’s signal processing complexity compared to time-domain methodologies. The results show we can emulate a real-time static coordinated scheduling proof-of-concept for one C-RAN composed of one RCC, three RRUs, and three UEs. In the end, it is evaluated the reproducibility and the scalability of synthetic networks composed of one RRU and at least one UE, without using software-defined radio units, reducing prototyping uncertainties of the physical hardware and the total price of the experiment.

Design Principles for Learning Environment based on STEAM Education

In this study, a learning environment based on STEAM theory was proposed to support and improve learners’ activities and achievements for convergent design education. The learning environment design influence STEAM education with intentional design and schedule coordination, schools can create informal environments that are crucial to STEAM education. The physical surroundings of the learning space should be applied to teaching methods and learning activity, especially for STEAM-based education, physical space conditions should support the learner’s design thinking and process. Furthermore, STEAM-based education environment should support a vast array of experiences that allow students to learn the context around ideas and skills. For spaces for learning environment based on STEAM, common design principles should be considered such as technology integration, safety and security, transparency, multipurpose space, and outdoor learning. Therefore, the learning environment based on STEAM needs flexible and mobile, connected, integrated, organized, flipped, and team-focused surroundings to support the learners understand, participate, cooperate, and accomplish the design process.

Scheduling Optimization of Prefabricated Buildings under Resource Constraints

Different from traditional construction project management, the prefabricated building (PB) engineering has a complicated restricted relationship in scheduling scheme, and the entire project is accomplished by multi-stage collaboration in construction process. Consequently, it is of great importance for project managers to make reasonable resources scheduling to avoid disruptions caused by resource unavailability. However, the poor interoperability and interactivity still results in diverse constraints, which limit the PB construction progress. Therefore, the aim of this paper is to establish a PB resource scheduling model that satisfying resource constraints and strengthening the PB dispatch time connection. The PB construction process is divided into assembly work space, logistics work space, and production work space where the construction time note is regarded as connection constraint and the three work spaces are restrained mutually. What's more, the optimal total amount of resources determination technology is presented to arrange the resource schedule in assembly work space to ensure the optimal resource quantity with the goals of the shortest construction time and the lowest cost. The dynamic scheduling coordination technology is put forward to logistics work space and production work space where the resource schedule is arranged with time node constraint. A high-rise building is presented as an example to illustrate the implementation of the proposed model. Results show that the presented method could effectively solve the problem of resource tension problem under the goal of the lowest cost as well as alleviate the shortage of multi-resource scheduling.

EFFECT OF KNOWLEDGE MANAGEMENT PRACTICES ON PERFORMANCE OF MOBILE TELEPHONE COMPANIES

Purpose: Knowledge management practices in general were found to influence organization performance as there is increased awareness of information that is critical to achieving the organization’s mission. The general objective of the study was to establish the effect of knowledge management practices on performance of mobile telephone companies.
 Methodology: The paper used a desk study review methodology where relevant empirical literature was reviewed to identify main themes and to extract knowledge gaps.
 Findings: The study concludes that knowledge management practices in general influences organization performance in various ways including, knowledgeable employees, better decision making in the organization, improved service offering to client, reduced operational costs, improved organizational competitiveness. This is mainly so because there is increased awareness of information that is critical to achieving the organization’s mission. The order of significance of the effect of knowledge management practices on performance of mobile telephone companies in starting with the most significant to the least is; knowledge creation, knowledge sharing, knowledge acquisition, knowledge implementation and knowledge storage respectively.
 Recommendations: The study points out that for effective organization administration organizations need to create a central repository system to store and retrieve information on organization reports cards, feedback on student progression, coordination of organization schedules, organization suspension, finances and other professional development which will have an overall effect on organization performance. Organizations should also install internet services and computers in order to share knowledge and improve the organization’s efficiency, performance, and competitiveness

Multi Objective Optimization Design of Building Construction Period based on BIM and Genetic Algorithm

China’s construction industry market competition is becoming increasingly fierce, which requires construction enterprises to gradually enhance the core competitiveness. Therefore, the construction period must be multi objective optimization (hereinafter referred to as MOO), which will improve the level of project management in the construction process. Through the MOO of construction period, we can achieve the overall cost optimization of construction projects. Through the coordination of construction project scheduling, we can improve the overall efficiency and efficiency of project operation, which will improve the utilization of resources and save the project cost. Genetic algorithm (hereinafter referred to as GA) can solve the adaptive global optimization probability search, which is a method to optimize the model process. By integrating GA into BIM platform, we introduce methods such as virtual construction and collision check, which can reasonably deal with complex MOO problems. The construction schedule and cost can be determined more quickly and reliably through the construction schedule. Therefore, this paper puts forward the MOO design among construction period, quality, safety and cost.

Research on the linkage mechanism and influencing factors of Jiangsu inland shipping and regional economic system

In order to cater to the new development paradigm, it is increasingly important of inland shipping system to expand domestic demand. Based on the linkage mechanism between inland shipping and regional economy, the index system of coordinated development is constructed, then the coupling coordination degree model of each index weight determined by entropy weighting method is calculated, the coupling correlation degree and coupling coordination scheduling between Jiangsu inland shipping system and regional economy system from 2009 to 2019 are enumerated, the key factors causing coupling effect in the two systems are analyzed by grey correlation analysis at the last. The result shows that the coupling between inland shipping and regional economy in Jiangsu Province has been at a high level for a long time, and the coupling coordination level has experienced a change from maladjustment to benign coupling, showing a trend of steady progress. Container throughput, cargo throughput, iron ore throughput, coal and its products throughput, GDP and per capita GDP are the key factors of the interaction between inland shipping and regional economy in Jiangsu Province. By revealing the linkage mechanism between inland shipping system and regional economic system, some suggestions to promote the coordinated development of regional systems can be put forward.

Heterogeneity of Total Factor Productivity of Export Tobacco Enterprises Under the Link of Tobacco Production Scheduling

Objectives: The production scheduling of tobacco enterprises belongs to the production arrangement level, that is, to the decision-making management level. Production scheduling chain management started relatively late in tobacco enterprises. Methods: By combining TFP and production scheduling chain through scheduling coordination function, they can achieve the same goal of organic link. This can enable tobacco enterprises to develop products with excellent quality and stable performance, so as to improve the export volume and create considerable economic benefits. Results: The TFP (total factor productivity) of enterprises from the perspective of heterogeneity to test the applicability of the new trade theory to China's agricultural export enterprises. It measures the TFP and its heterogeneity from the micro enterprise level, and shows that the average increasing rate TFP of China's agricultural export enterprises is 4.2%. At the regional level, the TFP growth rate in the western region is the highest. The TFP of state-owned enterprises is the lowest, with an average increasing rate of 6.6%. Conclusion: More attention should be paid to the active introduction of new factors to accelerate the establishment and development of a modern tobacco system. Moreover, advanced factors of the Internet, digitization, and intelligence should be combined to promote an in-depth integration of the producer services, advanced manufacturing industry, and modern agriculture to achieve free flow and effective allocation of various factors for technical progress.

Early Bird Scheme for Parking Management: How Does Parking Play a Role in the Morning Commute Problem

This paper extended the Vickrey’s point-queue model to study the early bird parking mechanism during morning commute peak hours. We not only investigated how commuters choose departure times in view of morning commute traffic congestion and the discounted early bird parking fee, but also analyzed the conditions which are determined for the existence of the user equilibrium in the analysis model provided in this paper. Moreover, the tendency of the total queuing time and the incremental parking pricing revenue was derived along with the different choice strategy between early bird parkers (ERPs) and regular parkers (RPs). The results showed that the number of commuters was jointly determined by the desired time and the bottleneck capacity for different schedules. Additionally, the method of fare incentive showed a better effect on reducing queue than the initial no-incentive method with the instantaneous travel demand. Most importantly, the incremental parking revenue can be increased by properly adjusting the parking pricing gap between ERPs and RPs. Our research not only provided several important propositions for the early bird parking mechanism but also included the optimal solutions for optimal parking pricing and schedule gap in two groups of parkers. This work is expected to promote the development of early bird parking to mitigate morning commute traffic congestion and motivate the related research of schedule coordination for regulating parking choice behavior in morning peak hours.

Flight schedule adjustment for hub airports using multi-objective optimization

Abstract Based on the concept of “passengers self-help hubbing,” we build a flight schedule optimization model where maximizing the number of feasible flight connections, indicating transfer opportunities, as one objective and minimizing total slot displacements as the other objective. At the same time, the “Demand Smoothing Model” is introduced into the flight schedule optimization model to reduce the queuing delays for arrival and departure flights. We take into account all aircraft itineraries, the difficulty level of schedule coordination, and the maximum displacement of any single flight acceptable to airlines when optimizing flight schedule. Given an original schedule, the model produces a feasible modified schedule that obeys the slot limits specified for an airport without canceling any flights, increases transfer opportunities, and improves on-time performance for hub airports while reducing interference with airline scheduling preferences. The model was verified with the operating data of the Urumqi international airport, and the results show that minor adjustments to flight schedules can increase the transfer opportunities of the airport and significantly reduce flight queuing delays.

Coordination of Charging Plug-in Electric Vehicles (PEV) in Electric Distribution Networks to Minimize Power Losses and Voltage Deviations

Plug-in Electric Vehicle (PEV) is a vehicle with a drive in the form of an electric motor and gets its energy source from a rechargeable battery. PEV (grid-to-vehicle, or G2V) charging activity can pose a risk to the distribution system when PEV is injected into the system. Charging PEV in the distribution system will cause the demand for electrical power to increase. Without a proper and optimal charging coordination system for the many PEVs that exist in the distribution network system, the following technical problems will arise in the network such as: occurrence of unusual and unwanted peak loads in power consumption, voltage sag, transformers or conductors overload, as well as the occurrence of high power system losses in the distribution system. This study discusses the optimization of PEV charging coordination scheduling in a distribution system by considering power losses and voltage deviations. To optimize the coordination of PEV charging, this study used a metaheuristic method called the Binary Particle Swarm Optimization (BPSO) which was then compared with the Binary Gray Wolves Optimization (BGWO) method. This scheme is simulated on the 20kV Pujon Feeder distribution system in Malang, Indonesia. The initial simulation results, at the time when the most loads were presented, showed 80 percent of PEV penetration, increase in power losses of 54.51 percent and voltage deviation of 9.82 percent. By using the BPSO method, the results showed power loss increase of 27.2 percent and voltage deviation of 7.75 percent. Meanwhile, by using the BGWO method the increase in power losses was 31.09 percent and the voltage deviation was 7.98 percent.

An infrastructure-assisted job scheduling and task coordination in volunteer computing-based VANET

Vehicular networks as the key enablers in Intelligent Transportation Systems (ITS) and the Internet of Things (IoT) are key components of smart sustainable cities. Vehicles as a significant component of smart cities have emerging in-vehicle applications that can assist in good governance for sustainable smart cities. Most of these applications are delay sensitive and demand high computational capabilities that are provided by emerging technologies. Utilizing the distributed computational resources of vehicles with the help of volunteer computing is an efficient method to fulfill the high computational requirements of vehicles itself and the other components of smart cities. Vehicle as a resource is an emerging concept that must be considered to address the future challenges of sustainable smart cities. In this paper, an infrastructure-assisted job scheduling and task coordination mechanism in volunteer computing-based VANET called RSU-based VCBV is proposed, which enhances the architecture of VANET to utilize the surplus resources of vehicles for task execution. We propose job scheduling and task coordination algorithms for different volunteer models. Further, we design and implement an adaptive task replication method to seek fault tolerance by avoiding task failures due to locations of vehicles. We propose a task replication algorithm called location-based task replication algorithm. Extensive simulations validate the performance of our proposed volunteer models while comparing average task execution time and weight ratios with existing work.

Coordinate scheduling of electric vehicles in charging stations supported by microgrids

When both the renewable energy sources (RES) generation and utilization occur simultaneously, energy storage costs can be reduced, and voltage oscillation and system instability caused by RES grid connection can be reduced. Therefore, this paper constructs a microgrid model that includes EVs, defines the charge and discharge capacity (CDC) of EVs, and uses the flexibility and dispatchability of EVs to overcome the intermittency and volatility of RES. By using the Monte Carlo method, this paper establish an EV driving model and proposes a two-stage process, that is, the first-stage is EV admission mechanism (EAM) and the second-stage is EV scheduling mechanism (ESM), to adapt to the uncertainty of RES, and maximize energy utilization and EV users satisfaction (Charging success rate). Through comparison with natural charging (NC) strategy, it is shown that the proposed two-stage process effectively overcomes the intermittency and volatility of RES and enables the stable operation of EVs in charging stations(CSs) supported by microgrids.

Late-week surgery and discharge to specialty care associated with higher costs and longer lengths of stay after elective lumbar laminectomy.

In a healthcare landscape in which costs increasingly matter, the authors sought to distinguish among the clinical and nonclinical drivers of patient length of stay (LOS) in the hospital following elective lumbar laminectomy-a common spinal surgery that may be reimbursed using bundled payments-and to understand their relationships with patient outcomes and costs. Patients ≥ 18 years of age undergoing laminectomy surgery for degenerative lumbar spinal stenosis within the Cleveland Clinic health system between March 1, 2016, and February 1, 2019, were included in this analysis. Generalized linear modeling was used to assess the relationships between the day of surgery, patient discharge disposition, and hospital LOS, while adjusting for underlying patient health risks and other nonclinical factors, including the hospital surgery site and health insurance. A total of 1359 eligible patients were included in the authors' analysis. The mean LOS ranged between 2.01 and 2.47 days for Monday and Friday cases, respectively. The LOS was also notably longer for patients who were ultimately discharged to a skilled nursing facility (SNF) or rehabilitation center. A prolonged LOS occurring later in the week was not associated with greater underlying health risks, yet it nevertheless resulted in greater costs of care: the average total surgical costs for lumbar laminectomy were 20% greater for Friday cases than for Monday cases, and 24% greater for late-week cases than for early-week cases ultimately transferred to SNFs or rehabilitation centers. A Poisson generalized linear model fit the data best and showed that the comorbidity burden, surgery at a tertiary care center versus a community hospital, and the incidence of any postoperative complication were associated with significantly longer hospital stays. Discharge to home healthcare, SNFs, or rehabilitation centers, and late-week surgery were significant nonclinical predictors of LOS prolongation, even after adjusting for underlying patient health risks and insurance, with LOSs that were, for instance, 1.55 and 1.61 times longer for patients undergoing their procedure on Thursday and Friday compared to Monday, respectively. Late-week surgeries are associated with a prolonged LOS, particularly when discharge is to an SNF or rehabilitation center. These findings point to opportunities to lower costs and improve outcomes associated with elective surgical care. Interventions to optimize surgical scheduling and perioperative care coordination could help reduce prolonged LOSs, lower costs, and, ultimately, give service line management personnel greater flexibility over how to use existing resources as they remain ahead of healthcare reforms.

A cooperative (or coordinated) multi-agency response to enhance the effectiveness of aerial bushfire suppression operations

An effective and efficient suppression of a bushfire is predicated on synchronised collaborative planning, information sharing, scheduling and tasks coordination between multiple agencies. This paper aims to develop a bushfire suppression optimisation model, which minimises the completion times and total costs within resource constraints. An algorithm is developed to tackle the highly complex operational response to bushfire suppression via aerial firefighting. A real case study of 2009 Black Saturday bushfires in Victoria is used to create the situational context and to derive model parameters. Three scenarios are designed to incorporate time and resource constraints to reflect a highly uncertain and dynamic situated bushfire environment. This study has generated bushfire suppression plans in emergency situations by improving resource utilisation efficiency and time scheduling. In the baseline scenario, the model indicates the ability of fire agencies to complete all operational activities, but in the scenarios where resource shortage and time limitations exist, the cost of unmet demands fell slightly. The outcomes of the proposed approach will help to enhance multi-agencies coordination in fire suppression evacuation plans to improve operational response and maximise geographic coverage of service delivery.

The Morning Commute Problem with Ridesharing When Meet Stochastic Bottleneck

This paper extends Vickrey’s point-queue model to study ridesharing behavior during a morning commute with uncertain bottleneck location. Unlike other ridesharing cost analysis models, there are two congestion cases and four dynamic departure patterns in our model: pre-pickup congestion case and post-pickup congestion case; both early pattern, both late pattern, late for pickup but early for work pattern, and early for pickup but late for work pattern. Analytical results indicate that the dynamic property of the mixed commuters equilibrium varies with the endogenous penetration rates associated with ridesharing commutes, as well as the schedule difference between pickup and work. This work is expected to promote the development of ridesharing to mitigate the traffic congestion and motivate related research of schedule coordination for regulating the ridesharing travel behavior in terms of the morning commute problem.

Data-driven two-stage stochastic optimization model for short-term hydro-thermal-wind coordination scheduling based on the dynamic extreme scenario set

A data-driven two-stage stochastic optimization model for solving short-term hydro-thermal-wind coordination scheduling problem with complicated time-coupled and space-related characteristics is proposed in this paper. The generation, emission and power fluctuation costs in the day-ahead scheduling stage and power regulation costs by hydro-thermal units, wind curtailment and load shedding costs in the real-time scheduling stage is formulated as the objective function of proposed model. Moreover, a dynamic extreme scenario generation and reduction method is introduced to deal with wind power uncertainty. The relationship between hydropower output, volume, inflow, discharge and upstream water for the multi-reservoir cascaded hydro plants is converted into a series of linear constraints, and the practical constraints of prohibited operation zones for thermal units are taken into account. As a result, the proposed model can be transformed into a mixed-integer linear programming problem to solve. Finally, case studies are carried out on the modified IEEE 24-bus system comprising of six thermal units, a multi-chain cascade of four hydro plants and one wind farm, and simulation results verify the effectiveness of the proposed coordination scheduling model and method. • Two-stage stochastic optimization for hydro-thermal-wind system is proposed. • Dynamic extreme scenario set is constructed to describe wind power uncertainty. • Spatio-temporal coupling characteristics of cascaded hydro plants is considered. • A mixed-integer linear programming is built for solving the scheduling problem.

Integrated scheduling of distributed service resources for complex equipment considering multiple on-site MRO tasks

The previous studies on service resource scheduling for maintenance, repair and operation (MRO) ignore the diverse service processes from different complex equipment and the coordination of task scheduling and resource allocation, which is less realistic when multiple tasks exist. In this work, we propose an integrated scheduling model of distributed service resources for on-site MRO, which simultaneously considers different service processes, service teams and material resources. The MRO service process is decomposed into multiple subtasks with hierarchical relationships (dependency and independency). Within the duration of the subtask, all multi-skill technicians in service team stay together and material resources are delivered from service providers. Resource allocation and task scheduling are integrated to minimise the makespan, the excessive human resources and the cost performance index of material resources. Further, we introduce six classic multi-objective evolutionary algorithms (MOEAs) to solve the scheduling problem, in which a novel and practical encoding method mixed with integers and decimals is developed. The design-of-experiment (DOE) method is used to determine the optimal combination of crucial parameters. Finally, 20 benchmark instances of multiple MRO tasks are tested. Experiment results show MOEA/D-DU could obtain higher quality scheduling solutions with relatively low computational costs in the integrated scheduling model.