Bus Driver Rostering via Extending Group Multirole Assignment

被引:0
|
作者
Lin, Xuewei [1 ]
Zhu, Haibin [2 ]
Liu, Dongning [1 ]
机构
[1] Guangdong Univ Technol, Sch Comp Sci & Technol, Guangzhou, Peoples R China
[2] Nipissing Univ, Dept Comp Sci & Math, North Bay, ON, Canada
来源
PROCEEDINGS OF THE 2024 27 TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN, CSCWD 2024 | 2024年
基金
加拿大自然科学与工程研究理事会; 中国国家自然科学基金;
关键词
Public transportation; Role-Based Collaboration (RBC); E-CARGO; Group Multirole Assignment (GMRA); Bus driver rostering; Multi-Criteria Decision Making;
D O I
10.1109/CSCWD61410.2024.10580473
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Although public transportation brings more and more convenience and practicality, it also presents greater safety hazards and economic concerns. How to select reasonable bus driver rostering (RBDR) for bus companies has become a pivotal resource optimization issue in public transportation by extending the Group Multirole Assignment (GMRA) model, this paper formalizes such a problem. Moreover, we propose multi-criteria decision making as a new method for driver evaluation, incorporating agent capability and satisfaction as important criteria. Additionally, in order to find the result solution more reasonably, the parameter change rules are obtained through multiple simulations. We first use the slope to find the steep drop point, and then use the variance and range to find the balance point, thereby obtaining the target parameter combination. The staged parameter selection method improves operating efficiency. Large-scale simulations indicate that the improved GMRA algorithm is suitable for different scenarios and can return multiple parameter combinations. By using this method, bus companies are able to select optimal parameter combinations in order to make diversified decisions based on transportation resources and development strategies.
引用
收藏
页码:1485 / 1490
页数:6
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