Local Rescheduling Research Articles

Method and algorithm for task allocation in a heterogeneous group of UAVs in a clustered field of targets

The article presents a method for distributing tasks to agents of a heterogeneous UAV group in a cluster field of tasks, when the number of tasks exceeds the number of agents by 5–20 times. The proposed task distribution method based on a three-stage procedure for distributing agents of different specializations among task clusters, taking into account the agent value function. To evaluate the effectiveness, the method compared with the greedy task distribution algorithm, the collective plan improvement algorithm, and the consensus-based linking algorithm with local rescheduling. 2400 experiments were carried out with different group sizes and randomly generated task maps, the results of which revealed the high efficiency of the proposed method. According to the results of the study, a relationship found between the efficiency of the method depending on the concentration of the number of tasks per agent. With an increase in the specific number of tasks per agent, the task execution time improves and the indicator of the path traveled by agents worsens. With a ratio of 5–10 agents per 100 tasks, the method shows the best results in terms of the parameters of the path traveled by agents and task execution time.

Coordinated railway traffic rescheduling with the Resource Conflict Graph model

The train rescheduling problem is quite a popular topic in the railway research community. Many approaches are available to reschedule traffic in a network partition, but very few works address the coordination of these partitions. In railway systems with very dense traffic, e.g. the Swiss one, it is not always possible to partition the network such that local rescheduling algorithms can work completely independently one from another. This paper proposes a coordination approach for adjacent local rescheduling algorithms. These algorithms are based on the Resource Conflict Graph model, which enables the representation of the interlocking system at a very fine granularity. Simulations on data from the Swiss Federal Railways show the validity of this approach to improve the consistency of decisions at the common boundaries of adjacent local rescheduling algorithms.

Effects of vertex insertion on local rescheduling in wireless sensor networks

Rescheduling has abundant issues yet to be explored. The local rescheduling problem in wireless sensor networks (WSNs) have been firstly addressed and investigated in this paper. The algorithms of local rescheduling have been proposed and evaluates the performance of reschedule solutions with different metrics. The solutions have to be under the limitation that the network should stay connected after the process of rescheduling. This paper introduces a theoretical bound of maximum degree after node insertion. Along with empirical results in real world settings, the results motivate the design of algorithms and give possible reasons why existing rescheduling algorithms do not work efficiently. Two local link rescheduling algorithms and one local broadcast rescheduling algorithm are developed as improvements. With different node densities and other critical parameters, simulations show that the developed algorithms greatly improve the ratio of finding proper solutions successfully in both types of scheduling compared with other existing simple algorithms.

Effects of Vertex Insertion on Local Rescheduling in Wireless Sensor Networks

Rescheduling has abundant issues yet to be explored. The local rescheduling problem in wireless sensor networks (WSNs) have been firstly addressed and investigated in this paper. The algorithms of local rescheduling have been proposed and evaluates the performance of reschedule solutions with different metrics. The solutions have to be under the limitation that the network should stay connected after the process of rescheduling. This paper introduces a theoretical bound of maximum degree after node insertion. Along with empirical results in real world settings, the results motivate the design of algorithms and give possible reasons why existing rescheduling algorithms do not work efficiently. Two local link rescheduling algorithms and one local broadcast rescheduling algorithm are developed as improvements. With different node densities and other critical parameters, simulations show that the developed algorithms greatly improve the ratio of finding proper solutions successfully in both types of scheduling compared with other existing simple algorithms.

Preventing Temporal Violations in Scientific Workflows: Where and How

Due to the dynamic nature of the underlying high-performance infrastructures for scientific workflows such as grid and cloud computing, failures of timely completion of important scientific activities, namely, temporal violations, often take place. Unlike conventional exception handling on functional failures, nonfunctional QoS failures such as temporal violations cannot be passively recovered. They need to be proactively prevented through dynamically monitoring and adjusting the temporal consistency states of scientific workflows at runtime. However, current research on workflow temporal verification mainly focuses on runtime monitoring, while the adjusting strategy for temporal consistency states, namely, temporal adjustment, has so far not been thoroughly investigated. For this issue, two fundamental problems of temporal adjustment, namely, where and how, are systematically analyzed and addressed in this paper. Specifically, a novel minimum probability time redundancy-based necessary and sufficient adjustment point selection strategy is proposed to address the problem of where and an innovative genetic-algorithm-based effective and efficient local rescheduling strategy is proposed to tackle the problem of how. The results of large-scale simulation experiments with generic workflows and specific real-world applications demonstrate that our temporal adjustment strategy can remarkably prevent the violations of both local and global temporal constraints in scientific workflows.

Disruption recovery model for berth and quay crane scheduling in container terminals

This article addresses the problem of recovering berth and quay crane (QC) schedules in container terminals when disruptions occur after a subset of operations has been processed. Firstly, models for simultaneous optimization of berth and QC schedules are developed. Then, two strategies, namely, QC rescheduling strategy and berth reallocation strategy are proposed to tackle disruptions and recover the berth and QC schedule, and models for the two strategies are developed respectively. To solve the disruption recovery models, algorithms based on local rescheduling and tabu search are designed. Finally, numerical experiments are provided to illustrate the validity of the proposed model and algorithms.

Applying Local Rescheduling in response to schedule disruptions

In realistic scenarios of disruption management the high number of potential options makes the provision of decision support—on how to get back on track—complex. It is thus desirable to reduce the size of the regarded problems by applying methods of partial rescheduling. As existing approaches (such as Affected Operations Rescheduling or Matchup Scheduling) mainly focus on production-specific problems, we propose Local Rescheduling (LRS) as a generic approach to partial rescheduling in this paper. It integrates previous research on partial rescheduling and local search in the context of complex project scheduling problems. LRS is based on the bidirectional incremental extension of a time window regarded for potential schedule modifications. Experiments show that LRS outperforms previous approaches.

Experimental studies on a local rescheduling procedure for dynamic routing of autonomous decentralized AGV systems

This paper addresses a local rescheduling procedure for a distributed routing system of multiple Automated Guided Vehicles in dynamic environments where the requests for transportation are given in real time. The effectiveness of the proposed method is investigated for a transportation system of 143 nodes and 10–30 AGV systems in a semi-conductor fabricating bay. A distributed and parallel routing system (DPRS) is implemented and tested on an experimental five mobile robot system. The results demonstrate that the proposed method can reduce the total computation time by 39% compared with the conventional method without lowering the performance level. It is also experimentally verified that the rescheduling procedure can deal with disturbances in a significantly short computation time.