Abstract. The Aircraft Recovery Problem (ARP) involves decisions concerning aircraft to flight assignments in situations where unforeseen events have disrupted the existing flight schedule, e.g. bad weather causing flight delays. The aircraft recovery problem aims to recover these flight schedules through a series of reassignments of aircraft to flights, delaying of flights and cancellations of flights. This article demonstrates an effective method to solve ARP. A heuristic is implemented, which is able to generate feasible revised flight schedules of a good quality in less than 10 seconds. This article is a product of the DESCARTES project, a project funded by the European Union between the Technical University of Denmark, British Airways and Carmen (see [1]).

To compete with alternative production methods, sheet metal working firms need to improve continuously. Improvement efforts do not solely focus on the production processes, but also on other aspects of the production chain. Production planning is one of those aspects that need to be optimized. The presented research focuses on production planning optimization for sheet metal shops with a cutting stage and a bending stage. The combination of the production plans of the individual processes does not result in a globally optimal production plan. Consequently, both processes need to be integrated for production planning. In this paper, an integer programming formulation is presented for the multiple-machine two-stage sheet metal shop production planning problem. Numerous real-life test cases are used to benchmark the approach against the current way of planning. To limit the computational time, a dedicated variable neighborhood search procedure is presented.Keywordsair bending, laser cutting, production planning, sheet metal working, variable neighborhood search.