Browsing by Author "Chen, Ta-Cheng"

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FCM based hybrid evolutionary computation approach for optimization power consumption by varying cars in EGCS
(2015-10-01)
Chen, Ta-Cheng
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Lee, An-Chen
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Huang, Shih-Lun
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機械工程學系
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Department of Mechanical Engineering
Elevators are the essential transportation tools in high buildings so that elevator group control system (EGCS) is developed to dynamically layout the schedule of elevators in a group. In this study, a fuzzy cognitive map (FCM) based computation approach by using particle swarm optimization (PSO) has been applied for estimating the minimum required elevators in EGCS so as to minimize the electricity consumption with predefined service quality. In literature, most of the studies were mostly focused on the scheduling strategy in order to have more efficient elevator dispatching or energy saving. However, the minimum numbers of elevators should be activated to sustain the required service quality. In other words, the maximum average waiting time for customers should be less than the predefined length of time while the minimum numbers of elevators are working in EGCS. The experimental results show that the performance of the proposed FCM based approach is feasible to estimate the required power consumption and average waiting time so as to decide the optimal numbers of elevators in EGCS. (C) 2015 Elsevier Inc. All rights reserved.
GA BASED HYBRID FUZZY RULE OPTIMIZATION APPROACH FOR ELEVATOR GROUP CONTROL SYSTEM
(2013)
Chen, Ta-Cheng
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Hsu, Yuan-Yong
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Lee, An-Chen
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Wang, Shiang-Yu
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機械工程學系
Elevators are the essential transportation tools in high buildings so that elevator group control system (EGCS) is developed to dynamically layout the schedule of elevators in a group. In this study, a fuzzy rule based intelligent EGCS optimized by genetic algorithm has been proposed where the rules with the corresponding parameters are generated optimally so as to maximize service quality. The experimental results show that the performance of our approach is superior to these of traditional approaches in the literature.
Multi-objective competitive location problem with distance-based attractiveness for two facilities
(2018-10-01)
Wang, Sheng-Chuan
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Lin, Chun-Cheng
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Chen, Ta-Cheng
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Hsiao, Han C. W.
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工業工程與管理學系
The multi-objective competitive location problem with distance-based attractiveness for two facilities (MOCLP-2 facilities) is introduced in this paper. A demand point is covered by two facilities, and the preferred facility satisfies the criteria of maximum attractiveness and minimum distance to the demand point. Facility attractiveness is defined as a distance-based coverage of the facility that can be full coverage, no coverage, or partial coverage of the demand point, depending on the within maximum full coverage radius, outside partial coverage radius between those two radii, respectively. The problem is formulated as a multi-objective optimization model to find a facility with maximum attractiveness and minimum distance. The contributions of this paper is that the problem can be tractably decided by the introduced non-dominated range (N.d. range) with less computation. Furthermore, extensive examples for facility selection and sensitivity analysis demonstrate its effectiveness and efficiency by the developed N.d. range.