We combine genetic algorithms and case-based reasoning principles to nd optimally directed solutions to open shop scheduling and open shop rescheduling problems. Appropriate solutions to open shop scheduling problems are injected into the genetic algorithm's population to speed up and augment genetic search on a related open shop rescheduling problem. Preliminary results indicate that the combi...

We introduce our Grid broker that uses SLAs in job submission with the aim of ensuring jobs are computed on time and on budget. We demonstrate our broker’s ability to perform negotiation and to select preferentially higher priority jobs, in a tender market and discuss the architecture that makes this possible. We additionally show the effects of rescheduling and how careful consideration is req...

Martine de Gerlache Prog Laboratory Vrije Universiteit Brussel Pleinlaan 2, 1050 Brussels Belgium Airline companies usually schedule their flights and crews well in advance to optimize their crew pools activities. Many events such as flight delays or the absence of a member require the crew pool rescheduling team to change the initial schedule (rescheduling). In this paper, we show that the neu...

In dynamic, stochastic manufacturing systems, production planners and manufacturing engineers can benefit from understanding how rescheduling strategies affect system performance. This knowledge will help these experts design and operate better manufacturing planning and control systems. This paper presents new analytical models that can predict the performance of rescheduling strategies and qu...

New algorithms based on mixed integer programming formulations are proposed for reactive scheduling in a dynamic, maketo-order manufacturing environment. The problem objective is to update a long-term production schedule subject to service level and inventory constraints, whenever the customer orders are modified or new orders arrive. Different rescheduling policies are proposed, from a total r...

In this study, we proposed a discrete teaching-learning-based optimisation (DTLBO) for solving the flowshop rescheduling problem. Five types of disruption events, namely machine breakdown, new job arrival, cancellation of jobs, job processing variation and job release variation, are considered simultaneously. The proposed algorithm aims to minimise two objectives, i.e., the maximal completion t...

Since disruptions in railway networks are inevitable, railway operators and infrastructure managers need reliable measures and tools for disruption management. Current literature on railway disruption management focuses most of the time on rescheduling one resource (timetable, rolling stock or crew) at the time. In this research, we describe an iterative framework in which all three resources a...

The main objective of this article is to gain fundamental understanding on the effect of real time information acquisition, on the traffic conditions of the Athens greater area. Activity scheduling is a dynamic process, where individuals often need to modify their schedule, as a result of new insights. Research so far hasn't analyzed the effect of traffic information acquisition, in activity sc...

Due to unforeseen problems, disruptions occur at railway passenger operators. Proper real-time crew management is needed to prevent disruptions to spread over space and time. Netherlands railways (NS) has algorithmic support from a solver to obtain good crew rescheduling solutions during big disruptions. However, small disruptions are still manually solved by human dispatchers who have limited ...