Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (170)
  • Open Access

    ARTICLE

    Optimal Scheduling of Multiple Rail Cranes in Rail Stations with Interference Crane Areas

    Nguyen Vu Anh Duy, Nguyen Le Thai, Nguyen Huu Tho*

    Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 15-31, 2024, DOI:10.32604/iasc.2024.038272

    Abstract In this paper, we consider a multi-crane scheduling problem in rail stations because their operations directly influence the throughput of the rail stations. In particular, the job is not only assigned to cranes but also the job sequencing is implemented for each crane to minimize the makespan of cranes. A dual cycle of cranes is used to minimize the number of working cycles of cranes. The rail crane scheduling problems in this study are based on the movement of containers. We consider not only the gantry moves, but also the trolley moves as well as the re-handle cases are also… More >

  • Open Access

    ARTICLE

    Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

    Ximin Cao*, Xinglong Chen, He Huang, Yanchi Zhang, Qifan Huang

    Energy Engineering, Vol.121, No.4, pp. 1067-1089, 2024, DOI:10.32604/ee.2023.046783

    Abstract Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals. Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system, a multi-time scale optimal scheduling strategy based on model predictive control (MPC) is proposed under the consideration of load optimization. First, load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature, and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost. Second, considering inter-day to… More >

  • Open Access

    ARTICLE

    MCWOA Scheduler: Modified Chimp-Whale Optimization Algorithm for Task Scheduling in Cloud Computing

    Chirag Chandrashekar1, Pradeep Krishnadoss1,*, Vijayakumar Kedalu Poornachary1, Balasundaram Ananthakrishnan1,2

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2593-2616, 2024, DOI:10.32604/cmc.2024.046304

    Abstract Cloud computing provides a diverse and adaptable resource pool over the internet, allowing users to tap into various resources as needed. It has been seen as a robust solution to relevant challenges. A significant delay can hamper the performance of IoT-enabled cloud platforms. However, efficient task scheduling can lower the cloud infrastructure’s energy consumption, thus maximizing the service provider’s revenue by decreasing user job processing times. The proposed Modified Chimp-Whale Optimization Algorithm called Modified Chimp-Whale Optimization Algorithm (MCWOA), combines elements of the Chimp Optimization Algorithm (COA) and the Whale Optimization Algorithm (WOA). To enhance MCWOA’s identification precision, the Sobol sequence… More >

  • Open Access

    ARTICLE

    An Improved Harris Hawk Optimization Algorithm for Flexible Job Shop Scheduling Problem

    Zhaolin Lv1, Yuexia Zhao2, Hongyue Kang3,*, Zhenyu Gao3, Yuhang Qin4

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2337-2360, 2024, DOI:10.32604/cmc.2023.045826

    Abstract Flexible job shop scheduling problem (FJSP) is the core decision-making problem of intelligent manufacturing production management. The Harris hawk optimization (HHO) algorithm, as a typical metaheuristic algorithm, has been widely employed to solve scheduling problems. However, HHO suffers from premature convergence when solving NP-hard problems. Therefore, this paper proposes an improved HHO algorithm (GNHHO) to solve the FJSP. GNHHO introduces an elitism strategy, a chaotic mechanism, a nonlinear escaping energy update strategy, and a Gaussian random walk strategy to prevent premature convergence. A flexible job shop scheduling model is constructed, and the static and dynamic FJSP is investigated to minimize… More >

  • Open Access

    ARTICLE

    Research on Flexible Job Shop Scheduling Based on Improved Two-Layer Optimization Algorithm

    Qinhui Liu, Laizheng Zhu, Zhijie Gao, Jilong Wang, Jiang Li*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 811-843, 2024, DOI:10.32604/cmc.2023.046040

    Abstract To improve the productivity, the resource utilization and reduce the production cost of flexible job shops, this paper designs an improved two-layer optimization algorithm for the dual-resource scheduling optimization problem of flexible job shop considering workpiece batching. Firstly, a mathematical model is established to minimize the maximum completion time. Secondly, an improved two-layer optimization algorithm is designed: the outer layer algorithm uses an improved PSO (Particle Swarm Optimization) to solve the workpiece batching problem, and the inner layer algorithm uses an improved GA (Genetic Algorithm) to solve the dual-resource scheduling problem. Then, a rescheduling method is designed to solve the… More >

  • Open Access

    ARTICLE

    A Strengthened Dominance Relation NSGA-III Algorithm Based on Differential Evolution to Solve Job Shop Scheduling Problem

    Liang Zeng1,2, Junyang Shi1, Yanyan Li1, Shanshan Wang1,2,*, Weigang Li3

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 375-392, 2024, DOI:10.32604/cmc.2023.045803

    Abstract The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems. It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives. The Non-dominated Sorting Genetic Algorithm III (NSGA-III) is an effective approach for solving the multi-objective job shop scheduling problem. Nevertheless, it has some limitations in solving scheduling problems, including inadequate global search capability, susceptibility to premature convergence, and challenges in balancing convergence and diversity. To enhance its performance, this paper introduces a strengthened dominance relation NSGA-III algorithm based on differential evolution… More >

  • Open Access

    ARTICLE

    Hybrid Hierarchical Particle Swarm Optimization with Evolutionary Artificial Bee Colony Algorithm for Task Scheduling in Cloud Computing

    Shasha Zhao1,2,3,*, Huanwen Yan1,2, Qifeng Lin1,2, Xiangnan Feng1,2, He Chen1,2, Dengyin Zhang1,2

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1135-1156, 2024, DOI:10.32604/cmc.2024.045660

    Abstract Task scheduling plays a key role in effectively managing and allocating computing resources to meet various computing tasks in a cloud computing environment. Short execution time and low load imbalance may be the challenges for some algorithms in resource scheduling scenarios. In this work, the Hierarchical Particle Swarm Optimization-Evolutionary Artificial Bee Colony Algorithm (HPSO-EABC) has been proposed, which hybrids our presented Evolutionary Artificial Bee Colony (EABC), and Hierarchical Particle Swarm Optimization (HPSO) algorithm. The HPSO-EABC algorithm incorporates both the advantages of the HPSO and the EABC algorithm. Comprehensive testing including evaluations of algorithm convergence speed, resource execution time, load balancing,… More >

  • Open Access

    ARTICLE

    Performance Prediction Based Workload Scheduling in Co-Located Cluster

    Dongyang Ou, Yongjian Ren, Congfeng Jiang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2043-2067, 2024, DOI:10.32604/cmes.2023.029987

    Abstract Cloud service providers generally co-locate online services and batch jobs onto the same computer cluster, where the resources can be pooled in order to maximize data center resource utilization. Due to resource competition between batch jobs and online services, co-location frequently impairs the performance of online services. This study presents a quality of service (QoS) prediction-based scheduling model (QPSM) for co-located workloads. The performance prediction of QPSM consists of two parts: the prediction of an online service’s QoS anomaly based on XGBoost and the prediction of the completion time of an offline batch job based on random forest. On-line service… More >

  • Open Access

    ARTICLE

    Two-Stage Optimal Scheduling of Community Integrated Energy System

    Ming Li1,*, Rifucairen Fu1, Tuerhong Yaxiaer1, Yunping Zheng1, Abiao Huang2, Ronghui Liu2, Shunfu Lin2

    Energy Engineering, Vol.121, No.2, pp. 405-424, 2024, DOI:10.32604/ee.2023.044509

    Abstract From the perspective of a community energy operator, a two-stage optimal scheduling model of a community integrated energy system is proposed by integrating information on controllable loads. The day-ahead scheduling analyzes whether various controllable loads participate in the optimization and investigates the impact of their responses on the operating economy of the community integrated energy system (IES) before and after; the intra-day scheduling proposes a two-stage rolling optimization model based on the day-ahead scheduling scheme, taking into account the fluctuation of wind turbine output and load within a short period of time and according to the different response rates of… More >

  • Open Access

    ARTICLE

    Low-Carbon Dispatch of an Integrated Energy System Considering Confidence Intervals for Renewable Energy Generation

    Yan Shi1, Wenjie Li1, Gongbo Fan2,*, Luxi Zhang1, Fengjiu Yang1

    Energy Engineering, Vol.121, No.2, pp. 461-482, 2024, DOI:10.32604/ee.2023.043835

    Abstract Addressing the insufficiency in down-regulation leeway within integrated energy systems stemming from the erratic and volatile nature of wind and solar renewable energy generation, this study focuses on formulating a coordinated strategy involving the carbon capture unit of the integrated energy system and the resources on the load storage side. A scheduling model is devised that takes into account the confidence interval associated with renewable energy generation, with the overarching goal of optimizing the system for low-carbon operation. To begin with, an in-depth analysis is conducted on the temporal energy-shifting attributes and the low-carbon modulation mechanisms exhibited by the source-side… More >

Displaying 1-10 on page 1 of 170. Per Page