An iterative approach to robust and integrated aircraft routing and crew scheduling

In airline scheduling a variety of planning and operational decision problems have to be solved. We consider the problems aircraft routing and crew pairing: aircraft and crew must be allocated to flights in a schedule in a minimal cost way. Although these problems are not independent, they are usually formulated as independent mathematical optimisation models and solved sequentially. This approach might lead to a suboptimal allocation of aircraft and crew, since a solution of one of the problems may restrict the set of feasible solutions of the problem solved later. Also, when minimal cost solutions are used in operations, a short delay of one flight can cause very severe disruptions of the schedule later in the day. We generate solutions that incur small costs and are also robust to typical stochastic variability in airline operations. We solve the two original problems iteratively. Starting from a minimal cost solution, we produce a series of solutions which are increasingly robust. Using data from domestic airline schedules we evaluate the benefits of the approach as well as the trade-off between cost and robustness. We extend our approach considering the aircraft routing problem together with two crew pairing problems, one for technical crew and one for flight attendants.     

Protecting BGP routes to top-level DNS servers

The Domain Name System (DNS) is an essential part of the Internet infrastructure and provides fundamental services, such as translating host names into IP addresses for Internet communication. The DNS is vulnerable to a number of potential faults and attacks. In particular, false routing announcements can deny access to the DNS service or redirect DNS queries to a malicious impostor. Due to the hierarchical DNS design, a single fault or attack against the routes to any of the top-level DNS servers can disrupt Internet services to millions of users. We propose a path-filtering approach to protect the routes to the critical top-level DNS servers. Our approach exploits both the high degree of redundancy in top-level DNS servers and the observation that popular destinations, including top-level DNS servers, are well-connected via stable routes. Our path-filter restricts the potential top-level DNS server route changes to be within a set of established paths. Heuristics derived from routing operations are used to adjust the potential routes over time. We tested our path-filtering design against BGP routing logs and the results show that the design can effectively ensure correct routes to top-level DNS servers without impacting DNS service availability.     

A model with a solution algorithm for the cash transportation vehicle routing and scheduling problem

Cash transportation vehicle routing and scheduling are essential for security carriers to minimize their operating costs and ensure safe cash conveyance. In real operations, to increase cash conveyance safety, there must be significant variation in daily cash transportation vehicle routes and schedules, making such vehicle routes and schedules difficult to formulate. However, for convenient planning purposes, security carriers normally plan such routes and schedules based on personal experience, without considering variations in routes and schedules from a system perspective. As a result, the obtained routes and schedules are neither safe nor efficient for transporting cash. In this study, a model is developed where the time–space network technique is utilized to formulate the potential movements of cash transportation vehicles among all demand points in the dimensions of time and space. This model incorporates a new concept of similarity of time and space for routing and scheduling, which is expected to help security carriers formulate more flexible routing and scheduling strategies. This is helpful to reduce the risk of robbery. Mathematically, the model is formulated as an integer multiple-commodity network flow problem. A solution algorithm, based on a problem decomposition/collapsing technique, coupled with the use of a mathematical programming software, is developed to efficiently solve the problem. The case study results show that our model and solution algorithm could be useful references for security carriers in actual practice.     

An integrated aircraft routing,crew scheduling and flight retiming model

In the integrated aircraft routing, crew scheduling and flight retiming problem, a minimum-cost set of aircraft routes and crew pairings must be constructed while choosing a departure time for each flight leg within a given time window. Linking constraints ensure that the same schedule is chosen for both the aircraft routes and the crew pairings, and impose minimum connection times for crews that depend on aircraft connections and departure times. We propose a compact formulation of the problem and a Benders decomposition method with a dynamic constraint generation procedure to solve it. Computational experiments performed on test instances provided by two major airlines show that allowing some flexibility on the departure times within an integrated model yields significant cost savings while ensuring the feasibility of the resulting aircraft routes and crew pairings.     

A computational study of Benders decomposition for the integrated aircraft routing and crew scheduling problem

The integrated aircraft routing and crew scheduling problem consists in determining a minimum-cost set of aircraft routes and crew pairings such that each flight leg is covered by one aircraft and one crew, and side constraints are satisfied. While some side constraints involve only crews or aircraft, linking constraints impose minimum connection times for crews that depend on aircraft connections. We propose an enhanced model incorporating robustness to handle these linking constraints and compare two Benders decomposition methods—one with the aircraft routing problem as the master problem and one with the crew pairing problem. We also study the impact of generating Pareto-optimal cuts on the speed of convergence of these methods. Computational experiments performed on test instances provided by two major airlines show that the proposed approach yields high-quality solutions in reasonable computing times.     

Modifying lines-of-flight in the planning process for improved maintenance robustness

As a part of their planning process, airlines construct lines-of-flight (LOFs ) - daily repeating sequences of flights, each of which will be flown by a single aircraft. In the week leading up to the actual day-of-operations, these LOFs are then assigned to specific aircraft (tails), forming multi-day aircraft routings that in turn enable the scheduling of routine maintenance checks. Operational disruptions, however, can lead to deviations from these routings, which in turn disrupt the maintenance plan. The goal of our research is to improve the construction of LOFs so as to increase the likelihood of being able to recover from maintenance disruptions without costly over-the-day aircraft swaps. We present a new metric, maintenance reachability (MR), which measures the robustness of a planned set of LOFs, and develop a mathematical programming approach to improving the MR of a given set of LOFs. We provide computational results based on data from a major U.S. carrier demonstrating that significant improvements in MR can be achieved with only a small number of changes to the original set of LOFs. Finally, we conclude by showing that even under imperfect input data, MR can be improved relative to a planned set of LOFs.     

Exploiting domain geometry in analogical route planning

Abstract. Automated route planning consists of using real maps to automatically find good map routes. Two shortcomings to standard methods are (1) that domain information may be lacking, and (2) that a ‘good’ route can be hard to define. Most on-line map representations do not include information that may be relevant for the purpose of generating good realistic routes, such as traffic patterns, construction, and one-way streets. The notion of a good route is dependent not only on geometry (shortest path),but also on a variety of other factors, such as the day and time, weather conditions,and perhaps most importantly,user-dependent preferences. These features can be learned by evaluating real-world execution experience. These difficulties motivate our work on applying analogical reasoning to route planning. Analogical reasoning is a method of using past experience to improve problem solving performance in similar new situations.Our approach consists of the accumulation and reuse of previously traversed routes. We exploit the geometric characteristics of the map domain in the storage, retrieval, and reuse phases of the analogical reasoning process. Our route planning method retrieves and reuses multiple past routing cases that collectively form a good basis for generating a new routing plan. To find a good set of past routes, we have designed a similarity metric that takes into account the geometric and continuous-valued characteristics of a city map. The metric evaluates its own performance and uses execution experience to improve its prediction of case similarity, adaptability and executability. The planner uses a replay mechanism to produce a route plan based on analogy with past routes retrieved by the similarity metric. We use illustrative examples and show some empirical results from a detailed on-line map of the city of Pittsburgh, containing over 18,000 intersections and 25,000 street segments.     

A Heuristic Algorithm for Hierarchical Hub-and-spoke Network of Time-definite Common Carrier Operation Planning Problem

Designing a heuristic approach to solve time-definite common carrier operation planning problem is the purpose of this research. The time-definite common carrier operation planning is implemented using the arcs and nodes of a hierarchical hub-and-spoke network. In light of the complexity involved in determining the types of the vehicles, as well as their associated routing and scheduling simultaneously, we design an algorithm, which employs the concept of tabu search to solve the network structure problem. The testing data are obtained from the second largest time-definite common carrier in Taiwan. When applied to the data of this test case company, the designed tabu search algorithm can obtain final solutions in a relatively short time regardless of the level of service required. Carriers can plan their operations according to the solutions on the operation networks. Although it is possible that the designed heuristic algorithm may converge to a local optimal solution, it can be a meaningful approach for the industrial application that emphasizes the value of time and can be satisfied with a near-optimal solution.     

A branch-and-price approach for a multi-period vehicle routing problem

In this paper, we consider tactical planning for a class of multi-period vehicle routing problems (MPVRP). This problem involves optimizing daily product collections from several production locations over a given planning horizon. In this context, a single routing plan for the whole horizon must be prepared, and the seasonal variations in the producers’ supplies must be taken into account. Production variations over the horizon are approximated using a sequence of periods, each corresponding to a production season, while the intra-period variations are neglected. We propose a mathematical model that is based on the two-stage a priori optimization paradigm. The first stage corresponds to the design of a plan which, in the second stage, takes the different periods into account. The proposed set partitioning-based formulation is solved using a branch-and-price approach. The subproblem is a multi-period elementary shortest path problem with resource constraints (MPESPPRC), for which we propose an adaptation of the dynamic-programming-based label-correcting algorithm. Computational results show that this approach is able to solve instances with up to 60 producers and five periods.     

Skewed general variable neighborhood search for the location routing scheduling problem

The integrated location routing scheduling problem is a variant of the well-known location routing problem. The location routing problem consists in selecting a set of depots to open and in building a set of routes from these depots, to serve a set of customers at minimum cost. In this variant, a vehicle can perform more than a single route in the planning period. As a consequence, the routes have to be scheduled within the workdays of each vehicle. The problem arises typically when routes are constrained to have a short duration. It happens for example within the boundaries of small geographic areas or in the transportation of perishable goods. In this paper, we propose a skewed general variable neighborhood search based heuristic to solve it. The algorithm is tested extensively and we show that it is efficient and provides the proven optimal solution in a significant number of cases. Moreover, it clearly outperforms a multi-start VND based heuristic that uses the same neighborhood structures.     

飞机维修计划优化模型与算法研究

分析了航空维修生产调度中的维修计划编制问题,仔细研究了飞机维修计划编制流程和约束条件,建立了飞机维修计划编制优化模型,不仅考虑了飞机维修资源的约束,同时还考虑了维修日期对效益的影响,能够快速确定每架飞机开始检修日期。为了求解模型,建立了离散粒子群优化算法,采用适合模型的粒子取值和速度变化方式。应用生产数据进行实际排产的实验结果表明,建立的模型和算法切实可行,可应用于生产实际,可大大提高生产调度自动化水平。     

Nonlinear identification and control of aircraft

The major goal of this paper is to approach and solve a spectrum of extremely important problems in nonlinear analysis, identification, optimization, and control of current and next generation advanced aircraft. High-performance aircraft must satisfy the required performances in the specified operational flight envelope at various attitudes and velocities, high-angle-of-attack regimes, all-weather, day and night operation. To improve mission effectiveness, ensure the specified flying and handling qualities (agility, manoeuvrability, controllability, and other pilotage quantities), guarantee survivability, damage adaptation and recovery, this paper reports a new, completely automated realtime motion control conceptual framework with failure accommodation features (self-repairing flight control). Innovative highly efficient identification and design methods are applied and verified. To attain the desired aircraft performance and expand the operational flight envelope at high-angle-of-attack regimes, identification and constrained optimization problems are solved using the developed motion control framework. An example is thoroughly studied to demonstrate the practical use and capabilities of the reported nonlinear design and identification procedures.     

Heuristics for tactical time slot management: a periodic vehicle routing problem view

In this study, we consider a tactical problem where a time slot schedule for delivery service over a given planning horizon must be selected in each zone of a geographical area. A heuristic search evaluates each schedule selection by constructing a corresponding tactical routing plan of minimum cost based on demand and service time estimates. At the end, the schedule selection leading to the best tactical routing plan is selected. The latter can then be used as a blueprint when addressing the operational problem (i.e., when real customer orders are received and operational routes are constructed). We propose two heuristics to address the tactical problem. The first heuristic is a three‐phase approach: a periodic vehicle routing problem (PVRP) is first solved, followed by a repair phase and a final improvement phase where a vehicle routing problem (VRP) with time windows is solved for each period of the planning horizon. The second heuristic tackles the problem as a whole by directly solving a PVRP with time windows. Computational results compare the two heuristics under various settings, based on instances derived from benchmark instances for the VRP with time windows.     

飞机多疲劳结构动态成组维修决策优化方法

以多个疲劳结构组成的飞机为对象,针对此类系统存在的维护困难、停机成本大等特点,研究多疲劳结构动态成组维修优化问题.在充分考虑结构停机维修用时以及多个疲劳结构之间维修相关性对于飞机使用率和维修费用的影响下,以维修费用和使用率为优化目标,以可靠度为约束,建立多疲劳结构动态成组维修决策优化模型.考虑飞机工作环境的严酷性和动态性,基于滚动时间轴模型,提出多疲劳结构动态成组维修决策优化方法.为了充分利用传感器获得的实时状态信息降低结构服役过程中损伤不确定性对维修计划制定的影响,并使维修计划能够适应复杂多变的动态环境,当每执行完一次停机维修活动或出现新的结构状态信息时,通过将维修决策时间窗口进行不断的滚动,使维修计划能够自适应地动态调整,达到无限规划周期的效果.     

Integrated maritime fleet deployment and speed optimization: Case study from RoRo shipping

When planning shipping routes, it is common to use a sequential approach where it is first assumed that each ship sails with a given service speed, and then later during the execution of the routes optimize the sailing speeds along the routes. In this paper we propose a new modeling approach for integrating speed optimization in the planning of shipping routes, as well as a rolling horizon heuristic for solving the combined problem. As a case study we consider a real deployment and routing problem in RoRo-shipping. Computational results show that the rolling horizon heuristic yields good solutions to the integrated problem within reasonable time. It is also shown that significantly better solutions are obtained when speed optimization is integrated with the planning of shipping routes.     

Improving robustness of rolling stock circulations in rapid transit networks

The rolling stock circulation depends on two different problems: the rolling stock assignment and the train routing problems, which up to now have been solved sequentially. We propose a new approach to obtain better and more robust circulations of the rolling stock train units, solving the rolling stock assignment while accounting for the train routing problem. Here robustness means that difficult shunting operations are selectively penalized and propagated delays together with the need for human resources are minimized. This new integrated approach provides a huge model. Then, we solve the integrated model using Benders decomposition, where the main decision is the rolling stock assignment and the train routing is in the second level. For computational reasons we propose a heuristic based on Benders decomposition. Computational experiments show how the current solution operated by RENFE (the main Spanish train operator) can be improved: more robust and efficient solutions are obtained.     

约束不均衡条件下车辆双层线路规划流动稳定性问题研究

双层线路在高峰期时,车辆规划计算最优解过程中为每个约束条件都分配一个最优解,会极大地浪费计算资源。车辆物流线路规划过程中,约束条件不均衡的天然特性,会导致规划过程车辆的流动稳定性受到影响。针对约束条件不均衡,对车辆双层线路规划流动稳定性影响的问题展开研究。构建了车辆物流线路双层规划Stackelberg模型,上层部分主要用于约束车辆物流线路的容量以及结构,排除不可用路线;下层部分主要对车辆物流线路实施均衡化配流,防止过多的车辆拥挤在同一路线中。利用模型将调度业务整合到高容量的路线中调度。在模型中加入调度资源缓存技术,保证调度过程的稳定性。实验结果表明：与使用单一模型求解相比,使用该模型进行调度业务疏导,可以在很大程度上获得更稳定的性能,解决了车辆物流线路规划流动稳定性问题。     

Application of genetic algorithm to computer-aided process planning in distributed manufacturing environments

In a distributed manufacturing environment, factories possessing various machines and tools at different geographical locations are often combined to achieve the highest production efficiency. When jobs requiring several operations are received, feasible process plans are produced by those factories available. These process plans may vary due to different resource constraints. Therefore, obtaining an optimal or near-optimal process plan becomes important. This paper presents a genetic algorithm (GA), which, according to prescribed criteria such as minimizing processing time, could swiftly search for the optimal process plan for a single manufacturing system as well as distributed manufacturing systems. By applying the GA, the computer-aided process planning (CAPP) system can generate optimal or near-optimal process plans based on the criterion chosen. Case studies are included to demonstrate the feasibility and robustness of the approach. The main contribution of this work lies with the application of GA to CAPP in both a single and distributed manufacturing system. It is shown from the case study that the approach is comparative or better than the conventional single-factory CAPP.     

A survey of models and algorithms for winter road maintenance. Part IV: Vehicle routing and fleet sizing for plowing and snow disposal

This is the last part of a four-part survey of optimization models and solution algorithms for winter road maintenance planning. The two first parts of the survey address system design problems for winter road maintenance. The third part concentrates mainly on vehicle routing problems for spreading operations. The aim of this paper is to provide a comprehensive survey of optimization models and solution methodologies for the routing of vehicles for plowing and snow disposal operations. We also review models for the fleet sizing and fleet replacement problems.     

LAMR:移动Ad hoc网络位置匿名的多路径路由协议

为有效减少移动Ad hoc网络路由协议开销并且实现网络路由的鲁棒性,引入位置匿名性和LAR局部定向洪泛机制。对Ad hoc网络中的ARMR协议(anonymous routing protocol with multiple routes)进行改进,提出一种新的基于匿名位置的多路径路由协议LAMR(location-based anonymous route protocol),LAMR与ARMR的不同之处有两点:a)融入匿名性的位置可减少路由分组在网络的全局洪泛;b)定向洪泛思想可避免路由回路产生。仿真实验结果表明,LAMR能比ARMR有效地提高路径请求成功率和降低路由请求时延。