A two stage heuristic algorithm for the integrated aircraft and crew schedule recovery problems

Airline disruptions incurred huge cost for airlines and serious inconvenience for travelers. In this paper, we study the integrated aircraft and crew schedule recovery problem. A two stage heuristic algorithm for the integrated recovery problem is proposed. In the first stage, the integrated aircraft recovery and flight-rescheduling model with partial crew consideration is built. This model is based on the traditional multi-commodity network model for the aircraft schedule recovery problem. The objective of this model also includes minimization of the original crew connection disruption. In the second stage, the integrated crew schedule recovery and flight re-scheduling model with partial aircraft consideration is built. We proposed a new multi-commodity model for the crew schedule recovery. The main advantage of such model is that it is much more efficient to integrate the flight-scheduling and aircraft consideration. New constraints are incorporated to guarantee that the aircraft connections generated in the stage 1 are still feasible. Two stages are run iteratively until no improvement can be achieved. Experimental results show that our method can provide better recovery solutions compared with the benchmark algorithms.     

A model for a reliable single allocation hub network design under massive disruption

Hub facilities may fail to operate in networks because of accidental failures such as natural disasters. In this paper, a quadratic model was presented for a reliable single allocation hub network under massive random failure of hub facilities which more than one hub may be disrupted in a route. It determines the location of the hub facilities and the primal allocation of non-hub nodes. It also determines the backup allocation in case of failure of the primal hub. First, a new lexicographic form of a bi-objective quadratic model is presented where the first objective maximizes served demands or equivalently, minimizes lost flows and the second objective minimizes total cost under a to massive disruption in the network. Then, by adding a structure-based constraint, the model is transformed to a single objective one. A linearization technique reported in the literature is applied on the quadratic model to convert it into classic linear zero–one mixed integer model while enhancing it by finding tighter bounds. The tight bounds’ technique is compared with other techniques in terms of computational time and its better performance was approved in some problem instances. Finally, due to the NP-hardness of the problem, an iterated local search algorithm was developed to solve large sized instances in a reasonable computational time and the computational results confirm the efficiency of the proposed heuristic, ILS can solve all CAB and IAD data set instances in less than 15 and 24 seconds, respectively. Moreover, the proposed model was compared with the classical hub network using a network performance measure, and the results show the increased efficiency of the model.     

A net-structure learning system for pattern description

This paper discusses a computer program that recognizes and describes two-dimensional patterns composed of subpatterns. The program also recognizes all patterns in a scene consisting of several patterns.

Patterns are stored in a learned hierarchical, net-structure memory. Weighted links between memory nodes represent subpattern/pattern relationships. Both short term and permanent memories are used.

Pattern recognition is accomplished with a serial heuristic search algorithm, which attempts to search memory and compute input properties efficiently. Without special processing, the program can be asked to look for all occurrences of a specified pattern in a scene.     

Managing disruption in an imperfect production–inventory system

In this paper, a disruption recovery model is developed for an imperfect single-stage production–inventory system. For it, the system may unexpectedly face either a single disruption or a mix of multiple dependent and/or independent disruptions. The system is usually run according to a user defined production–inventory policy. We have formulated a mathematical model for rescheduling the production plan, after the occurrence of a single disruption, which maximizes the total profit during the recovery time window. The model thereby generates a revised plan after the occurrence of the disruption. The mathematical model, developed for a single disruption, is solved by using both a pattern search and a genetic algorithm, and the results are compared using a good number of randomly generated disruption test problems. We also consider multiple disruptions, that occur one after another as a series, for which a new occurrence may or may not affect the revised plan of earlier occurrences. We have developed a new dynamic solution approach that is capable of dealing with multiple disruptions on a real-time basis. Some numerical examples and a set of sensitivity analysis are presented to explain the usefulness and benefits of the developed model. The proposed quantitative approach helps decision makers to make prompt and accurate decisions for managing disruption.     

A virtual disk environment for providing file system recovery

File system recovery (FSR) is a kind of recovery facility that allows users to roll back the file system state to a previous state. In this paper, we present a virtual disk environment (VDE) which allows previous write operations to a hard disk to be undone, and previous version of files to be recovered. It can be used to recover the file system quickly even when computer system suffers the serious disaster such as system crash or boot failure. The VDE is same as virtual disk in the virtual machine (VM) environment in some way, but it can be applied to the environment without VM supports. Algorithms for implementing the VDE are presented and its implementation on Windows platform is discussed. Based on the implementation, the experimental results of the VDE performance are analyzed. Comparing with other FSRs, the main advantage of the VDE is low overhead and high recovery speed.     

A supply chain disruption recovery strategy considering product change under COVID-19

A recent global outbreak of Corona Virus Disease 2019 (COVID-19) has led to massive supply chain disruption, resulting in difficulties for manufacturers on recovering their supply chains in a short term. This paper presents a supply chain disruption recovery strategy with the motivation of changing the original product type to cope with that. In order to maximize the total profit from product changes, a mixed integer linear programming (MILP) model is developed with combining emergency procurement on the supply side and product changes by the manufacturer as well as backorder price compensation on the demand side. The model uses a heuristic algorithm based on ILOG CPLEX toolbox. Experimental results show that the proposed disruption recovery strategy can effectively reduce the profit loss of manufacturer due to late delivery and order cancellation. It is observed that the impact of supply chain disruptions is reduced. The proposed model can offer a potentially useful tool to help the manufacturers decide on the optimal recovery strategy whenever the supply chain system experiences a sudden massive disruption.     

Workpiece recognition and inspection by a model-based scene analysis system

A scene analysis system for the recognition and inspection of overlapping workpieces in visually noisy scenes is described. It consists of a preprocessing algorithm based on an edge-following operator and a model-based analysis algorithm. In the preprocessing stage, which is not described in detail, features such as corners, straight lines, circles and circular arcs are extracted and described by a few parameters. In the analysis stage, the pattern features extracted by the preprocessing algorithm are used to synthesize, in model-guided fashion, a prototype of the workpiece, which is continuously checked against the model. A similarity measure indicates the match between model and scene. Besides topographical features, the analysis makes use of grey levels, textural measures and values representing colors.Results obtained with different, partly occluded workpieces are given.     

Dump技术在Solaris系统恢复中的应用研究

对Solaris操作系统核心部分、数据文件部分的备份和恢复方法进行了描述,论述了Dump技术在Solaris系统恢复中的应用.分析表明,Dump技术是Solaris操作系统恢复技术中最为快捷有效的方法之一,它可以使系统快速地恢复正常,保证系统的稳定运行.     

Charged system search for optimal design of frame structures

The charged system search (CSS) algorithm is utilized for design of frame structures. The algorithm is inspired by the laws in physics. The CSS utilizes a number of charged particles which influence each other based on their fitness values and their separation distances considering the governing law of Coulomb. A comparison between the characteristics of the CSS algorithm and other well-known meta-heuristics is performed to indicate their similarities and differences. Some benchmark frame examples are optimized with the CSS algorithm. Comparison of the results of CSS with some other meta-heuristic algorithms shows the robustness of the new algorithm.     

Knowledge-based modeling for disruption management in urban distribution

Disruption management in urban distribution is the process of achieving a new distribution plan in order to respond to a disruption in real time. Experienced schedulers can respond to disruptions quickly with common sense and past experiences, but they often achieve the new distribution plan by a fuzzy, sometimes inconsistent, and not well-understood way. The method is limited when the problem becomes large scale or more complicated. In this case, optimization techniques consisting of models and algorithms may complement it. However, as the distribution system’s state changes constantly with the plan-executing process and disruptions are diversified, real-time modeling is very difficult. Hence in order to achieve the real-time modeling process, the research in the paper focuses on a knowledge-based modeling method, which combines the knowledge of experienced schedulers with the OR knowledge concerning models and algorithms. Policies, algorithms and models are represented by proper knowledge representation schemes in order to support automated or semi-automated modeling by computers. The modeling process is demonstrated by a case to show how the different kinds of knowledge representation schemes cooperate with each other to support the modeling process. In the knowledge-based modeling process, based on the knowledge of experienced schedulers, a qualitative policy for handling the disruption based on the current distribution system’s state is achieved firstly; and then based on OR knowledge, the corresponding model and algorithm are constructed to quantitatively optimize the policy. The integration of the two kinds of knowledge not only effectively supports the real-time modeling process, but also combines the advantages of both to achieve more practical and scientific solutions to different kinds of disruptions occurring under different distribution system’s states.     

Adapting the behavior of a job-shop scheduling system

Factory scheduling consists in assigning resources (e.g. machines) and start and end times to operations. Our work is concerned with the problems of schedule generation and schedule revision when unanticipated events occur on the factory floor. SONIA is a knowledge-based scheduling system provided with a blackboard architecture for coordinating the activation of various scheduling and analyzing knowledge sources. In this paper, we focus on the various behaviors these knowledge sources can have and we gather a collection of conclusions regarding the use of various backtracking strategies and the control of constraint propagation.     

数据中心容灾系统研究

数据中心承载着对业务运行休戚相关的应用,而业务有续和灾难恢复策略已经成为各个行业关注的焦点.在信息时代发展的今天,系统的破坏和数据的丢失所带来的损失是难以估量的,通过对数据中心容灾系统常用的容灾技术进行比较,结合某大型数据中心客灾系统建设,设计了基于Snap-mirror技术的容灾系统.实现了数据反向复制时只复制灾难期间变化的数据而不是所有的数据,同时可以保证恢复时间最短.解决了传统数据恢复,需要进行整个系统的回迁的问题.     

Disruption management in a constrained multi-product imperfect production system

Over several decades, production and inventory systems have been widely studied in different aspects, but only a few studies have considered the production disruption problem. In production systems, the production may be disrupted by priorly unknown disturbance and the entire manufacturing plan can be distorted. This research introduces a production-disruption model for a multi-product single-stage production-inventory system. First, a mathematical model for the multi-item production-inventory system is developed to maximize the total profit for a single-disruption recovery-time window. The main objective of the proposed model is to obtain the optimal manufacturing batch size for multi-item in the recovery time window so that the total profit is maximized. To maintain the matter of multi-product, budget and space constraints are used. A genetic algorithm and pattern search techniques are employed to solve this model and all randomly generated test results are compared. Some numerical examples and sensitivity analysis are given to explain the effectiveness and advantages of the proposed model. This proposed model offers a recovery plan for managers and decision-makers to make accurate and effective decisions in real time during the production disruption problems.     

噪声图象中提取边界的随机启发式搜索方法

在噪声图象中如何有效地提取边界是图象分析领域中的难点。启发式搜索的方法常常用于提取边界,但是,这种方法由于采用固定的起始点、固定的引导度量以及对图象仅进行一次性搜索,对噪声往往很敏感,为此提出了一种随机启发式搜索算法,该方法随机地选取起始点,并依照引导度量的概率反复地进行随机搜索获得各种可能的边界轨迹,然后进行各搜索轨迹的积累自增强,最后根据自增强积累统计结果获得边界。大量的实验结果证明,在噪声图象中,随机启发式搜索方法可以在提取出有意义边界的同时有效地抑制噪声。     

取证系统中数据恢复关键技术研究

磁盘中已删除文件在未被覆盖之前,其存储方式为连续和离散存储。针对连续存储提出了一种准确匹配已删除文件首簇高16位算法,并重点分析离散存储碎片,提出了一种基于部分匹配预测算法PPMC来重构磁盘上已删除文件碎片的模型。采用PPMC算法确定出任意两个碎片的相邻性概率值,然后再通过剪枝技术,将不可能的分支裁减,逐步加工处理,重构出一个有完整顺序的原文件。     

A periodic tabular policy for scheduling of a single stage production-inventory system

In this paper, we consider scheduling of a multi-item single stage production-inventory system in the presence of uncertainty regarding demand patterns, production times and switchover times. For a given specification of base-stock levels of individual items and under (S − 1, S) requests for replenishment policy, a mathematical program to minimize long-run average system wide costs is formulated. We derive approximations for the first two moments of demand over lead time using residual service analysis of vacation queue models. Subsequently, we develop an approximate convex program for the original cost model and determine optimal production frequencies for individual types. Based on these relative frequencies, we determine a table size and devise an efficient heuristic to construct a tabular sequence in which individual items appear according to their respective absolute frequencies and items are positioned such that variance of their inter-visit times is minimized. A numerical study that demonstrates effectiveness of the proposed policy against cyclic policies is given.     

针对FreeBSD的网络灾难备份系统设计与实现*

探讨了灾难备份与FreeBSD操作系统联合使用的重要性,并提出和实现了一种针对FreeBSD的容灾平台.该平台能够提供磁盘高速镜像、磁盘监控和集系统恢复于一体的容灾系统.     

A tabu search algorithm with a new neighborhood structure for the job shop scheduling problem

Tabu search (TS) algorithms are among the most effective approaches for solving the job shop scheduling problem (JSP) which is one of the most difficult NP-complete problems. However, neighborhood structures and move evaluation strategies play the central role in the effectiveness and efficiency of the tabu search for the JSP. In this paper, a new enhanced neighborhood structure is proposed and applied to solving the job shop scheduling problem by TS approach. Using this new neighborhood structure combined with the appropriate move evaluation strategy and parameters, we tested the TS approach on a set of standard benchmark instances and found a large number of better upper bounds among the unsolved instances. The computational results show that for the rectangular problem our approach dominates all others in terms of both solution quality and performance.     

A算法在梵塔问题中的应用

介绍了启发式搜索A算法及其在梵塔问题中的应用,利用极值方法设计了一种估价函数,提高了搜索效率,减少了搜索量。     

考虑传播过程的应急网络控制系统故障恢复

紧急情况下, 应急网络控制系统为人员提供远程控制能力, 但系统仍存在一定故障率, 且故障影响会利用系统灵活传输机制快速扩散, 因此研究如何在故障快速扩散的情况下对系统实施故障控制, 对保证系统安全运行具有重要意义. 本文提出考虑传播过程的应急网络控制系统故障恢复策略. 首先, 基于复杂网络模型建立故障传播模型, 定义传播路径上的故障强度, 将分析故障信息关键传播过程转化为查找系统最大可能传播路径的问题, 进而在连接边的故障传播属性乘积大于终止条件时, 找到最大概率故障传播路径, 有针对地布置故障检测点; 再根据检测到的故障形式及检测点位置生成故障恢复策略库, 结合系统可调度性和故障恢复效果, 确定最优故障恢复策略. 最后, 以舰船应急火炮控制系统构建案例, 验证方法可行性, 并设置多节点故障, 验证算法鲁棒性, 仿真结果表明, 在不同故障情形下均能制定最优故障恢复策略.