Results 21 to 30 of about 55,996 (318)
Mathematical and Computational Applications, 2021 Many real-world optimization problems involving several conflicting objective functions frequently appear in current scenarios and it is expected they will remain present in the future.
Mercedes Perez-Villafuerte +4 more
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Appointment Scheduling for Health Examination Customers Based on Two-stage Stochastic Simulation Optimization Algorithm [PDF]
Jisuanji gongcheng, 2021 In many health examination agencies,the unreasonable scheduling mechanisms make customers stay in the queue for longer time.This paper presents the study on the scheduling of health examination customers under stochastic service time.Using an appointment
LIU Dan, GENG Na
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International Journal of Computational Intelligence Systems, 2022 Linguistic preference relations (LPRs) and its variations served for different decision-making situations are significantly important instruments of qualitative decision-making.
Guolin Wu, Zhibin Wu
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Research on security-constrained unit commitment based on an improved ordinal optimization algorithm
Frontiers in Energy Research, 2023 It is of great significance for the development of intermittent renewable energy and the marketization of electricity to study an efficient and accurate algorithm for solving the unit commitment problem with security constraints.
Zhi Zhang, Guobin Xu, Nan Yang
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Journal of Cloud Computing: Advances, Systems and Applications, 2023 Efficient utilization of available computing resources in Cloud computing is one of the most challenging problems for cloud providers. This requires the design of an efficient and optimal task-scheduling strategy that can play a vital role in the ...
Monika Yadav, Atul Mishra
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A method for finding a least-cost corridor on an ordinal-scaled raster cost surface
Annals of GIS, 2023 The least-cost path problem is a widely studied problems in geographic information science. In raster space, the problem is to find a path that accumulates the least amount of cost between two locations based on the assumptions that the path is a one ...
Lindsi Seegmiller, Takeshi Shirabe
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Energies, 2019 The uncertainty of wind power brings many challenges to the operation and control of power systems, especially for the joint operation of multiple wind farms.
Nan Yang +6 more
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Incremental Sparse Bayesian Ordinal Regression [PDF]
, 2018 Ordinal Regression (OR) aims to model the ordering information between different data categories, which is a crucial topic in multi-label learning. An important class of approaches to OR models the problem as a linear combination of basis functions that ...
de Rijke, Maarten, Li, Chang
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Evaluation and Optimization of a Traditional North-Light Roof on Industrial Plant Energy Consumption
Energies, 2013 Increasingly strict energy policies, rising energy prices, and a desire for a positive corporate image currently serve as incentives for multinational corporations to reduce their plants’ energy consumption.
Qianchuan Zhao +3 more
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Distributed Support Vector Ordinal Regression over Networks
Entropy, 2022 Ordinal regression methods are widely used to predict the ordered labels of data, among which support vector ordinal regression (SVOR) methods are popular because of their good generalization.
Huan Liu, Jiankai Tu, Chunguang Li
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