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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Harrath, Youssef Alyusuf, Jood Ghulam, Zeena Aldoseri, Muna The Beacom College of Computer and Cyber Sciences Dakota State University MadisonSD United States College of Information Technology University of Bahrain Bahrain

ISBN: (纸本)9798350369106

This study analyzed the transportation issues at the University of Bahrain Sakhir campus, where a bus system with an unorganized and fixed number of buses allocated each semester was in place. Data was collected through a survey, on-site observations, and student schedules to estimate the number of buses needed. The study was limited to students who require to move between buildings for academic purposes and not those who choose to ride buses for other reasons. An algorithm was designed to calculate the optimal number of buses for each time slot, and for each day. This solution could improve transportation efficiency, lower costs, enhance students' mobility experience, and decrease CO2 emissions. A series of recommendations were provided to university officials including the need for further research to examine creating new routes and implementing express buses. © 2024 IEEE.

关键词： scheduling algorithms

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Efficient Solution for Exam Timetabling Problem: A Case Study of the University of Sharjah 17

Efficient Solution for Exam Timetabling Problem: A Case Stud...

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17th International Conference on Developments in eSystems Engineering, DeSE 2024

作者： Lulu, Israa Alowais, Hind Turky, Ayad Harous, Saad Hussain, Abir College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Electrical Engineering Department University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9798350368697

Efficient exam timetabling is a crucial aspect of academic management, particularly in a university with many programs and many students, such as the University of Sharjah. This paper addresses the challenges of exam scheduling at the University of Sharjah by proposing two metaheuristic algorithms: the simulated annealing algorithm and the genetic algorithm. Both algorithms were evaluated based on conflict resolution, location diversity, and runtime. The experimental results indicate that both algorithms performed well overall, showcasing the potential of advanced optimization techniques in enhancing academic operations and student experiences. Both algorithms optimize course assignments within capacity and scheduling constraints, ensuring fair and efficient exam scheduling. While the simulated annealing algorithm showed potential in diversifying course-location assignments, the genetic algorithm outperformed the simulated annealing algorithm in terms of runtime efficiency, contributing to efficient exam scheduling processes. Future research could explore hybrid approaches for further enhancements. © 2024 IEEE.

关键词： scheduling algorithms

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Greedy algorithms for Heterogeneous Drone Delivery Packing in the Cloud-assisted Intelligent Transportation System 16

Greedy Algorithms for Heterogeneous Drone Delivery Packing i...

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16th International Conference on COMmunication Systems and NETworkS, COMSNETS 2024

作者： Mohapatra, Satyajit Nayak, Sanjeet Kumar Iiitdm Kancheepuram Department of Cse Chennai India

ISBN: (纸本)9798350383119

Intelligent Transportation Systems (ITS) paves the way towards a futuristic world. A systematic, quick and trouble-free transportation system is in demand for last-mile deliveries to support the logistic companies. With the help of drones, last-mile delivery becomes quite viable for ensuring deliveries through difficult landscapes and heavy traffic. However, as the number of warehouses with multiple drones increase, it becomes challenging for the logistic companies to efficiently manage these drones with limited battery and weight carrying capacity. The warehouses thus require an efficient governance to ensure deliveries with least number of drones, known as drone delivery packing problem. To address the issue of drone delivery packing with variable battery and weight lifting capacity, in this work, we present the heterogeneous drone delivery packing problem (HDPP) for a cloud-assisted ITS. The objective of HDPP is to minimise the number of heterogeneous drones for a warehouse. Further, we prove that HDPP is NP-hard problem and present an Integer Linear Programming (ILP) based modeling technique for finding optimal solution. Subsequently, we devise two heuristic methods (CD-MaxB and CD-MinB) which provide us near optimal results quickly. Finally, we perform a comparison of our heuristic algorithms with baseline approaches and show their competency in solving large sized instances quickly. The deviation of performance of CD-MaxB and CD-MinB are less than 12% when compared to optimal solution. © 2024 IEEE.

关键词： Cloud Computing Intelligent Transportation System Optimization algorithms scheduling algorithms Truck Drone Delivery Unmanned Aerial Vehicles

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A CP-SAT Approach for Academic Resource Timetabling in Higher Education Institutions: A Case Study at a Major Public University 21

A CP-SAT Approach for Academic Resource Timetabling in Highe...

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21st International Conference on Information Technology Based Higher Education and Training, ITHET 2024

作者： Moreira, Eber Junio Borges De Freitas, Sergio Antonio Andrade University of Brasília PPCA/UnB Brasília Brazil University of Brasília CEDIS/UnB and PPCA/UnB Brasília Brazil

ISBN: (纸本)9798331516635

In this paper, an interactive model for academic resource timetabling using constraint programming with Google OR-Tools' CP-SAT is developed and tested. This model is currently under experimentation at a major public university, where eleven real instances have been tested. Preliminary results suggest that the model is well-suited for enhancing academic resource management to accommodate established constraints and preferences. The findings of this study offer a scalable solution to university scheduling, providing administrators with the opportunity to enhance the efficient allocation of resources in complex educational settings. © 2024 IEEE.

关键词： scheduling algorithms

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Service Improvements in Real-Time Uniprocessor scheduling With Single Errors

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IEEE ACCESS 2021年 9卷 43540-43550页

作者： Schmidt, Robert Garcia-Ortiz, Alberto Univ Bremen Inst Electrodynam & Microelect D-28359 Bremen Germany

Mixed-criticality scheduling in modern deeply embedded mission and safety-critical systems needs to consider delivered service, that is, the runtime in low criticality mode. If the change into a higher criticality mode is triggered by the first overrunning job, the service is severely reduced. With earliest deadline first with virtual deadlines for single errors (EDF-VD-SE) we show how to reserve additional time to tolerate a single overrunning job by formulating and solving an optimization problem, and that EDF-VD-SE is feasible without assumptions about error probabilities for safety guarantees. We conduct extensive simulation experiments to report on average doubled service figures, and show how EDF-VD-SE results in a nearly constant acceptance rate of random task systems.

关键词： Task analysis Switches Processor scheduling Real-time systems Licenses Software Schedules Real-time systems scheduling algorithms system recovery

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Heuristic Task scheduling Algorithm Based on Rational Ant Colony Optimization

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Chinese Journal of Electronics 2025年第2期23卷 311-314页

作者： Xiaodong Zhang Xiaoyan Cui Shizhuo Zheng School of Electrical Engineering Beijing Jiaotong University Beijing China Automation School Beijing University of Posts and Telecommunications Beijing China

Distributed data stream processing system is NP-complete problem to assign tasks to any number of nodes handling the task scheduling. Even for substantially reducing scheduling scale, the problem still cannot be avoided. This paper takes advantage of the classical algorithm (ant colony optimization) of heuristic methods to simulate the global task scheduling problem of distributed system. Rational improvement on ant colony optimization path-finding for the memory and CPU usage of each node achieves load balancing in a short time. It gives the sub-optimal solution of the global task scheduling. The experiments show that the data stream processing system we proposed has good real-time characteristics and stability.

关键词： Ant colony optimization scheduling algorithms Heuristic algorithms Distributed databases Load management Stability analysis scheduling Real-time systems NP-complete problem Research and development

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An Energy-Efficient Hybrid scheduling Algorithm for Task scheduling in the Cloud Computing Environments

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IEEE ACCESS 2021年 9卷 117325-117337页

作者： Walia, Navpreet Kaur Kaur, Navdeep Alowaidi, Majed Bhatia, Kamaljeet Singh Mishra, Shailendra Sharma, Naveen Kumar Sharma, Sunil Kumar Kaur, Harsimrat Chandigarh Univ Dept Comp Sci & Engn Ajitgarh 140413 Punjab India Sri Guru Granth Sahib World Univ Dept Comp Sci & Engn Fatehgarh Sahib 140407 Punjab India Majmaah Univ Coll Comp & Informat Sci Dept Informat Technol Al Majmaah 11952 Saudi Arabia Govind Ballabh Pant Inst Engn & Technol Dept Elect & Commun Engn Pauri Garhwal 246194 Uttarakhand India IK Gujral Punjab Tech Univ Dept Elect Engn Jalandhar 144603 Punjab India IKGPTU Dept Elect & Commun Engn Jalandhar 144603 Punjab India CTIEMT Shahpur Jalandhar 144020 Punjab India

The main intent of the cloud computing to provide utilities to the demands of the users that are booming day by day. To meet the requirements, existing scheduling algorithms focus on the improving the performance and neglecting the energy consumed to fulfill those demands. Hence, we propose a new Hybrid scheduling Algorithm (HS) which is based on the Genetic Algorithm (GA) and Flower Pollination based Algorithm (FPA) for cloud environments. The proposed scheduling algorithm has surpassed in terms of performance across various parameters, i.e. completion time, resource utilization, cost of computation, and energy consumption for both cloud environments than the existing scheduling algorithms (GA and FPA). The simulation results revealed that HS has demonstrated maximum resource utilization with minimum energy consumption in less completion time for the execution of the tasks as compared to the existing scheduling algorithms in both environments. The simulation results have shown that HS has utilization of the resources, 36% better than GA and 16% better than FPA in homogeneous environment whereas in heterogenous environment, HS has performed 12% better than GA and 3.8% better than FPA. The performance of HS has an improvement of 2.6% from FPA and 6.9% from the GA for completion time in homogeneous environment whereas the completion time of the HS is reduced by 17.8% from FPA and 33.7% from GA in heterogeneous environment. For energy consumption, HS has improved 22% than FPA and 11% from GA in the homogeneous environment and HS is 4% better than FPA and 14% from GA in heterogeneous environment.

关键词： Cloud computing scheduling algorithms Task analysis Genetic algorithms Resource management Energy consumption Computational modeling Cloud computing energy resource scheduling tasks

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Energy-Aware Concurrent Data Aggregation scheduling for Wireless Powered IoT Leveraging Hypergraph Theory

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IEEE WIRELESS COMMUNICATIONS LETTERS 2021年第11期10卷 2464-2468页

作者： Jiao, Xianlong Lou, Wei Guo, Songtao Li, Yong Yao, Junmei Gu, Fuqiang Ma, Junchao Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen 518060 Peoples R China Shenzhen Technol Univ Coll Big Data & Internet Shenzhen 518118 Peoples R China

This letter investigates the minimum-delay data aggregation scheduling problem for wireless powered Internet of Things (WPIoT). Unlike traditional Internet of Things (IoT), WPIoT devices should harvest enough energy before data transmission or reception. Hence, many existing solutions for traditional IoT cannot be directly applied to WPIoT. In this letter, we propose a delay-efficient algorithm by fully considering the energy features and cumulative interference effects of WPIoT. This algorithm constructs the data aggregation tree based on the fewest-children-first rule and implements a novel energy-aware concurrent link scheduling method leveraging the hypergraph theory. This novel link scheduling method can satisfy both the residual energy constraint and signal interference constraint. The performance of our algorithm is evaluated by extensive experiments based on a real-world dataset under non-linear energy harvesting models with both perfect and imperfect channel state information. The results confirm the superiority of our algorithm over the baseline algorithms.

关键词： Data aggregation Interference Wireless communication Logic gates Approximation algorithms Delays scheduling Wireless powered IoT scheduling algorithms data aggregation tree construction data aggregation link scheduling hypergraph theory

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Dynamic Charging scheduling Optimization for Electric Vehicles Based on Quantum SWARM Algorithm 7

Dynamic Charging Scheduling Optimization for Electric Vehicl...

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7th Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2022

作者： Zhang, Guoyu Dai, Mian Zhao, Shuai Zhao, Pengchao Intelligence Data Catarc Adc Tianjin China

ISBN: (数字)9781665485197

ISBN: (纸本)9781665485197

A dynamic scheduling method based on Quantum SWARM is proposed for electric vehicles charging in the relative disordered traffic environment. It aims to maximum the overall charging efficiency considering the realistic individual competition and group collaboration. The result of the simulation validation shows that for 100 random target power-anxiety clients, Quantum SWARM algorithm could iterate in 1 step with reduction of error comparison around 87%, which could provide a guaranteed optimal allocation planing for charging station, and a derived control logic for swarm intelligent agents such as autonomous electric vehicles. © 2022 IEEE.

关键词： scheduling algorithms

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Design of OMNET++ for Input-queued switching Networks 5

Design of OMNET++ for Input-queued switching Networks

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5th International Symposium on Computer Engineering and Intelligent Communications, ISCEIC 2024

作者： Cheng, Bowen Zhou, Weibin School of Electronic Information and Automation Tianjin University of Science and Technology Tianjin300222 China

ISBN: (纸本)9798331518677

To evaluate the performance of iterative scheduling algorithms in input queuing and switching networks, this study constructs a specialized simulation platform using OMNET++ software suit. Adopted through a modular and object-oriented approach, the platform supports various scheduling algorithms and can accurately simulate the complete process from data generation to output, including the processing of different types of service flows. By implementing the iSLIP, DRRM, EiSLIP and EDRRM algorithms, the platform's network-level performance simulation capability is verified under different load conditions, demonstrating its potential in promoting the research of network architecture optimization and scheduling strategies, which is of great significance in promoting the theoretical and practical advancement of network technology. This platform fills the gap of existing simulation software in specific areas and provides an effective tool for the research of iterative scheduling algorithms. © 2024 IEEE.

关键词： scheduling algorithms

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