基于资源约束的地铁运营施工任务调度研究
Metro Maintenance Tasks Scheduling Considering Resource Constraints
罗钦 1黄杉 1宋剑伟 2曾翠峰 2陈菁菁 1李伟1
作者信息
- 1. 深圳技术大学,城市交通与物流学院,广东深圳 518118;广东省高校轨道交通智慧运维工程技术开发中心,广东深圳 518118
- 2. 深圳地铁运营集团有限公司,广东深圳 518040
- 折叠
摘要
针对地铁运营施工资源有限、时间严格、任务繁重等特点,本文以地铁运营施工任务调度为研究对象,建立运营施工调度优化模型与算法.模型以任务优先级、施工人员和施工工区限制等为约束条件,以完工时间最小化、施工人员工作负荷均衡化为目标;设计一种联合线性规划与资源交叉(CPLEX-ROC)的混合求解算法;通过对某实际地铁运营线路展开案例研究,验证模型和算法的可行性与先进性.案例研究结果表明:相较于人工调度、遗传算法(GA)、教学优化算法(TLBO)方法,最大完工时间分别降低32.90%、15.11%和10.75%;施工人员工作负荷均衡指标相较GA、TLBO分别优化了15.44%和10.62%.计算结果验证了本模型能够提升地铁运营施工任务整体作业效率,同时实现施工人员工作负荷均衡.
Abstract
Metro maintenance construction is normally undertaken with heavy workload,limited resources,and strict timelines.This paper focuses on the metro maintenance task plan to establish an optimization model and algorithm for maintenance scheduling.The model takes task priority,person,and workspace capacity constraints as constraints,and aims to minimize the makespan and balances person workload.A hybrid algorithm is designed in combination of the linear programming and resource crossover(CPLEX-ROC).A case study verifies the feasibility and effectiveness of the model and algorithm.The results show that compared to manual scheduling,genetic algorithm(GA),and Teaching-learning-based optimization(TLBO)methods,the proposed method reduces the makespan reduced by 32.90%,15.11%,and 10.75%respectively.The person workload balance is improved by 15.44%compared to GA,and improved by 10.62%compared to the TLBO.The proposed method improves the overall operation efficiency of metro maintenance tasks and balances the personal work load in the constructions.
关键词
铁路运输/运营施工调度/整数规划/项目调度/多目标优化Key words
railway transportation/maintenance tasks scheduling/integer programming/project scheduling/multi-objective optimization引用本文复制引用
基金项目
国家自然科学基金青年科学基金(52208441)
广东省普通高校创新团队(2022KCXTD027)
广东省重点建设学科科研能力提升项目(2021ZDJS108)
出版年
2024
NETL
NSTL
维普
万方数据