Two-Stage Metaheuristic Framework Based on Irregular Contours Matching for Outsourced Aircraft Maintenance Parking Stand Allocation Problem

IF 6.4 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Automation Science and Engineering Pub Date : 2024-09-24 DOI:10.1109/TASE.2024.3457773
Ben Niu;Gaocheng Cai;Tianwei Zhou
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Abstract

With the increase in aircraft maintenance orders and heterogeneity of aircraft irregular shapes, outsourced aircraft maintenance companies urgently need a more efficient and tailored intelligent aircraft parking allocation method. However, existing methods could be improved in lightweight handling of non-overlapping constraints and effective use of problem-specific heuristics. To tackle these challenges and achieve a more rational allocation of parking stands, a bi-objective optimization model involving rotation angles is firstly constructed to maximize hangar utilization and safety margin, and is decomposed into two single-objective optimization problems via a lexicographic method. To efficiently solve this model, problem characteristics of “irregular contours matching” are analyzed. Furthermore, a series of mechanisms that fully utilize the problem characteristics are designed, thus integrating a two-stage metaheuristic framework based on irregular contours matching. These mechanisms include an aircraft parking strategy based on geometric fit for rationally locating aircraft parking positions and mitigating the dimensional explosion problem, a metaheuristic optimizer with similar insertion neighborhood operation for enhancing the hangar utilization, and a fast safety margin optimization algorithm based on binary searching iterator. Experimental studies conducted on 18 real-world instances show that the proposed framework outperforms several state-of-the-art algorithms, as well as the dynamic search algorithm automatically selected by the CPLEX optimizer. Note to Practitioners—This paper investigates an aircraft parking stand allocation problem that originated in outsourced aircraft maintenance companies. The goal of the problem is to maximize the hangar utilization and safety margin. Existing aircraft parking stand allocation methods ignore the lightweight handling of non-overlapping constraints, optimal configuration of rotation angles and safety margins, and effective utilization of problem-specific heuristics. Thus the allocation efficiency could be further improved when coping with large-scale order requirements. This paper constructs a mathematical optimization model with limited rotation angles, and introduces a concise geometric tool to address aircraft collision problem. Furthermore, a two-stage metaheuristic framework based on problem characteristics is proposed to solve the model efficiently. The superiority of the present method was verified on 18 real-instances with various hangar sizes and maintained aircraft. It is believed that this method effectively improves maintenance resource utilization, reducing labor and maintenance costs of outsourced aircraft maintenance companies.
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基于不规则轮廓匹配的外包飞机维修停机位分配问题的两阶段元优化框架
随着飞机维修订单的增加和飞机不规则形状的异质性,飞机维修外包公司迫切需要一种更高效、更有针对性的智能飞机停放分配方法。然而,现有的方法可以在轻量级处理非重叠约束和有效使用特定于问题的启发式方面得到改进。为了解决这些问题,实现更合理的停机位配置,首先构建了考虑转角的双目标优化模型,以最大限度地提高机库利用率和安全裕度,并通过词典法将其分解为两个单目标优化问题。为了有效地求解该模型,分析了“不规则轮廓匹配”问题的特点。在此基础上,设计了一系列充分利用问题特征的机制,整合了一个基于不规则轮廓匹配的两阶段元启发式框架。这些机制包括基于几何拟合的飞机停放策略,以合理定位飞机停放位置并缓解维度爆炸问题;基于类似插入邻域操作的元启发式优化器,以提高机库利用率;基于二进制搜索迭代器的快速安全裕度优化算法。在18个实际实例上进行的实验研究表明,所提出的框架优于几种最先进的算法,以及CPLEX优化器自动选择的动态搜索算法。给从业人员的说明——本文研究了一个起源于外包飞机维修公司的飞机停机位分配问题。问题的目标是最大化机库利用率和安全裕度。现有的飞机停机位分配方法忽略了非重叠约束的轻量化处理、旋转角度和安全裕度的最优配置以及问题特定启发式的有效利用。在处理大规模订单需求时,可以进一步提高分配效率。本文建立了一个旋转角度有限的数学优化模型,并引入了一种简洁的几何工具来解决飞机碰撞问题。在此基础上,提出了一种基于问题特征的两阶段元启发式框架来有效地求解该模型。通过18架不同机库尺寸和维修飞机的实例验证了该方法的优越性。认为该方法有效地提高了维修资源的利用率,降低了飞机维修外包公司的人工和维修成本。
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来源期刊
IEEE Transactions on Automation Science and Engineering
IEEE Transactions on Automation Science and Engineering 工程技术-自动化与控制系统
CiteScore
12.50
自引率
14.30%
发文量
404
审稿时长
3.0 months
期刊介绍: The IEEE Transactions on Automation Science and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. T-ASE welcomes results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, security, service, supply chains, and transportation. T-ASE addresses a research community willing to integrate knowledge across disciplines and industries. For this purpose, each paper includes a Note to Practitioners that summarizes how its results can be applied or how they might be extended to apply in practice.
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