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Your search keyword '"Sang, Hong-Yan"' showing total 171 results
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171 results on '"Sang, Hong-Yan"'

27. An Improved SMA Algorithm for Solving Global Optimization Problems

Author

Guo, Heng-wei, Sang, Hong-yan, Li, Jun-qing, Han, Yu-yan, Zhang, Biao, Meng, Lei-lei, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Huang, De-Shuang, editor, Jo, Kang-Hyun, editor, Li, Jianqiang, editor, Gribova, Valeriya, editor, and Bevilacqua, Vitoantonio, editor

Published
2021
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39. A Developed NSGA-II Algorithm for Multi-objective Chiller Loading Optimization Problems

Author

Duan, Pei-Yong, Wang, Yong, Sang, Hong-yan, Wang, Cun-gang, Qi, Min-yong, Li, Jun-qing, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Huang, De-Shuang, editor, Bevilacqua, Vitoantonio, editor, and Premaratne, Prashan, editor

Published
2016
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40. A Discrete Invasive Weed Optimization Algorithm for the No-Wait Lot-Streaming Flow Shop Scheduling Problems

Author

Sang, Hong-Yan, Duan, Pei-Yong, Li, Jun-Qing, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Huang, De-Shuang, editor, Bevilacqua, Vitoantonio, editor, and Premaratne, Prashan, editor

Published
2016
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48. An improved artificial bee colony algorithm for addressing distributed flow shop with distance coefficient in a prefabricated system.

Author

Li, Jun-qing, Bai, Shun-Chang, Duan, Pei-yong, Sang, Hong-yan, Han, Yu-yan, and Zheng, Zhi-xin

Subjects
BEES algorithm, FLOW shops, DISTRIBUTED algorithms, PRECAST concrete, MAXIMUM power point trackers, DISTANCES, MODULAR construction
Abstract

This paper proposes an improved artificial bee colony (IABC) algorithm for addressing the distributed flow shop considering the distance coefficient found in precast concrete production system, with the minimisation of the makespan. In the proposed algorithm, each solution is first represented by a two-dimensional vector, where the first dimensional vector is the factory and the second dimensional vector lists the operation scheduling sequence of each factory. Second, considering the distributed problem feature, a distributed iterated greedy heuristic (DIG) is developed where destruction and construction processes are designed in detail while considering the distributed structures. Third, an efficient population initialisation method that considers the factory workload balance is presented. Then, a local search approach that randomly replaces two factories with two randomly selected jobs and that finds an optimal position for the two inserted operations via the DIG method is proposed. For the canonical ABC algorithm, using the DIG approach, the main three parts are improved, namely, the employee, onlooker, and scout bees. Finally, the proposed algorithm is tested on sets of extended instances based on the well-known benchmarks. Through an analysis of the experimental results, the highly effective proposed IABC algorithm is compared to several efficient algorithms drawn from the literature. [ABSTRACT FROM AUTHOR]

Published
2019
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49. Bi-objective optimization using an improved NSGA-II for energy-efficient scheduling of a distributed assembly blocking flowshop.

Author

Niu, Wei, Li, Jun-qing, Jin, Hui, Qi, Rui, and Sang, Hong-yan

Subjects
SCHEDULING, ENERGY consumption
Abstract

In this study, an Energy-Efficient Distributed Assembly Blocking FlowShoP (EEDABFSP) is considered. An improved Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is developed to solve it. Two objectives have been considered, i.e. minimizing the maximum completion time and total energy consumption. To begin, each feasible solution is encoded as a one-dimensional vector with the factory assignment, operation scheduling and speed setting assigned. Next, two initialization schemes are presented to improve both quality and diversity, which are based on distributed assembly attributes and the slowest allowable speed criterion, respectively. Then, to accelerate the convergence process, a novel Pareto-based crossover operator is designed. Because the populations have different initialization strategies, four different mutation operators are designed. In addition, a distributed local search is integrated to improve exploitation abilities. Finally, the experimental results demonstrate that the proposed algorithm is more efficient and effective for solving the EEDABFSP. [ABSTRACT FROM AUTHOR]

Published
2023
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