Sistem Penjadwalan Otomatis Kuliah Mahasiswa

Scheduling in the scope of education is a common thing done especially at the university level. There are many factors that must be considered in the process of scheduling lectures because it is very different when compared with the schedule at the level of basic education. The classes are taken dynamically by students because they are not determined from the start by the university. Limitations of space and time of the lecturers make the preparation of the schedule will take a relatively long time and require more precision. The availability of this application to facilitate the actors involved in the process of scheduling lectures, because classes will be automatically generated by the system so that the scheduling process will be more effective and efficient. Benefits for students is when doing online KRS, the system will offer a choice of courses that can be taken and will not happen collision schedule. This web-based application is developed using Python programming language with Django framework on backend and Twitter bootstrap on the frontend. The results of this study is a system that can perform scheduling automatically

Dynamic charging management for electric vehicle demand responsive transport

With the climate change challenges, transport network companies started to electrify their fleet to reduce CO2 emissions. However, such an ecological transition brings new research challenges for dynamic electric fleet charging management under uncertainty. In this study, we address the dynamic charging scheduling management of shared ride-hailing services with public charging stations. A two-stage charging scheduling optimization approach under a rolling horizon framework is proposed to minimize the overall charging operational costs of the fleet, including vehicles' access times, charging times, and waiting times, by anticipating future public charging station availability. The charging station occupancy prediction is based on a hybrid LSTM (Long short-term memory) network approach and integrated into the proposed online vehicle-charger assignment. The proposed methodology is applied to a realistic simulation study in the city of Dundee, UK. The numerical studies show that the proposed approach can reduce the total charging waiting times of the fleet by 48.3% and the total charged the amount of energy of the fleet by 35.3% compared to a need-based charging reference policy

Fuzzy Feedback Scheduling of Resource-Constrained Embedded Control Systems

The quality of control (QoC) of a resource-constrained embedded control system may be jeopardized in dynamic environments with variable workload. This gives rise to the increasing demand of co-design of control and scheduling. To deal with uncertainties in resource availability, a fuzzy feedback scheduling (FFS) scheme is proposed in this paper. Within the framework of feedback scheduling, the sampling periods of control loops are dynamically adjusted using the fuzzy control technique. The feedback scheduler provides QoC guarantees in dynamic environments through maintaining the CPU utilization at a desired level. The framework and design methodology of the proposed FFS scheme are described in detail. A simplified mobile robot target tracking system is investigated as a case study to demonstrate the effectiveness of the proposed FFS scheme. The scheme is independent of task execution times, robust to measurement noises, and easy to implement, while incurring only a small overhead.Comment: To appear in International Journal of Innovative Computing, Information and Contro

Real time resource scheduling within a distributed collaborative design environment

Operational design co-ordination is provided by a Virtual Integration Platform (VIP) that is capable of scheduling and allocating design activities to organisationally and geographically distributed designers. To achieve this, the platform consists of a number of components that contribute to the engineering management and co-ordination of data, resources, activities, requirements and processes. The information required to schedule and allocate activities to designers is defined in terms of: the designers' capability to perform particular design activities; commitment in terms of the design activities that it is currently performing, and capacity to perform more than one design activity at the same time as well as the effect of increased capacity on capability. Previous approaches have been developed by the authors to automatically allocate resources to activities [1-3], however these approaches have generally been applied either within the context of real-time allocation of computational resources using automated design tools, or in the planning of human resources within future design projects and not for the real-time allocation of activities to a combination of human and computational resources. The procedure presented here is based upon this previous research and involves: the determination of the design activities that need to be undertaken on the basis of the goals that need to be achieved; identification of the resources that can undertake these design activities; and, the use of a genetic algorithm to optimally allocate the activities to the resources. Since the focus of the procedure is toward the real-time allocation of design activities to designers, additional human issues with respect to scheduling are considered. These human issues aspects include: consideration of the improvement in performance as a result of the experience gained from undertaking the activity; provision of a training period to allow inexperienced designers the opportunity to improve their performance without their performance being assessed; and the course of action to take when a designer is either unwilling or unable to perform an activity