Non-linear great deluge with learning mechanism for solving the course timetabling problem

International audienc

Distributed scheduling based on multi-agent systems and optimization methods

The increasing relevance of complex systems in dynamic environments has received special attention during the last decade from the researchers. Such systems need to satisfy products or clients desires, which, after accomplished might change, becoming a very dynamic situation. Currently, decentralized approaches could assist in the automation of dynamic scheduling, based on the distribution of control functions over a swarm network of decision-making entities. Distributed scheduling, in an automatic manner, can be answered by a service coordination architecture of the different schedule components. However, it is necessary to introduce the control layer in the solution, encapsulating an intelligent service that merge agents with optimization methods. Multi-agent systems (MAS) can be combined with several optimization methods to extract the best of the two worlds: the intelligent control, cooperation and autonomy provided by MAS solutions and the optimum offered by optimization methods. The proposal intends to test the intelligent management of the schedule composition quality, in two case studies namely, manufacturing and home health care.FCT - Fundação para a Ciência e a Tecnologia (UID/CEC/00319/2019

Dynamic SLA Negotiation in Autonomic Federated Environments

Abstract. Federated computing environments offer requestors the ability to dynamically invoke services offered by collaborating providers in the virtual service network. Without an efficient resource management that includes Dynamic SLA Negotiation, however, the assignment of providers to customer’s requests cannot be optimized and cannot offer high reliability without relevant SLA guarantees. We propose a new SLA-based SERViceable Metacomputing Environment (SERVME) capable of matching providers based on QoS requirements and performing autonomic provisioning and deprovisioning of services according to dynamic requestor needs. This paper presents the SLA negotiation process that includes on-demand provisioning and uses an object-oriented SLA model for large-scale service-oriented systems supported by SERVME. An initial reference implementation in the SORCER environment is also described

Susceptibility of optimal train schedules to stochastic disturbances of process times

This work focuses on the stochastic evaluation of train schedules computed by a microscopic scheduler of railway operations based on deterministic information. The research question is to assess the degree of sensitivity of various rescheduling algorithms to variations in process times (running and dwell times). In fact, the objective of railway traffic management is to reduce delay propagation and to increase disturbance robustness of train schedules at a network scale. We present a quantitative study of traffic disturbances and their effects on the schedules computed by simple and advanced rescheduling algorithms. Computational results are based on a complex and densely occupied Dutch railway area; train delays are computed based on accepted statistical distributions, and dwell and running times of trains are subject to additional stochastic variations. From the results obtained on a real case study, an advanced branch and bound algorithm, on average, outperforms a First In First Out scheduling rule both in deterministic and stochastic traffic scenarios. However, the characteristic of the stochastic processes and the way a stochastic instance is handled turn out to have a serious impact on the scheduler performance

Optimal spare parts management for vessel maintenance scheduling

Condition-based monitoring is used as part of predictive maintenance to collect real-time information on the healthy status of a vessel engine, which allows for a more accurate estimation of the remaining life of an engine or its parts, as well as providing a warning for a potential failure of an engine part. An engine failure results in delays and down-times in the voyage of a vessel, which translates into additional cost and penalties. This paper studies a spare part management problem for maintenance scheduling of a vessel operating on a given route that is defined by a sequence of port visits. When a warning on part failure is received, the problem decides when and to which port each part should be ordered, where the latter is also the location at which the maintenance operation would be performed. The paper describes a mathematical programming model of the problem, as well as a shortest path dynamic programming formulation for a single part which solves the problem in polynomial time complexity. Simulation results are presented in which the models are tested under different scenarios