Fleet Assignment Using Population-Based Incremental Learning

被引：0
作者：
Kobayashi, Yuto [1 ]
Fukuyama, Yoshikazu [1 ]
机构：
[1] Meiji Univ, Sch Interdisciplinary Math Sci, Tokyo, Japan
来源：
2021 60TH ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS OF JAPAN (SICE) | 2021年
关键词：
Fleet assignment; population; based incremental learning; meta-heuristics; evolutionary computation; DISTRIBUTION ALGORITHM;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposes fleet assignment using population-based incremental learning (PBIL). Effectiveness of the proposed PBIL based method is verified by comparing with the conventional reactive tabu search (RTS) based method and the actual flight operation data. It is verified that the proposed PBIL based method can reduce costs more than the conventional RTS based method and the actual flight operation data.
引用
收藏
页码：868 / 873
页数：6
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