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BACKGROUND Planning the health-care workforce required to meet the health needs of the population, while providing service levels that maximize the outcome and minimize the financial costs, is a complex task. The problem can be described as assessing the right number of people with the right skills in the right place at the right time, to provide the right(More)
The possibilities of combining simulation and optimization are vast and the appropriate design highly depends on the problem characteristics. Therefore, it is very important to have a good overview of the different approaches. The taxonomies and classifications proposed in the literature do not cover the complete range of methods and overlook some important(More)
lotsizing and scheduling with sequence-dependent, period overlapping and non triangular setups. Disclaimer UWE has obtained warranties from all depositors as to their title in the material deposited and as to their right to deposit such material. UWE makes no representation or warranties of commercial utility, title, or fitness for a particular purpose or(More)
From long to short term planning, decision processes inherent to operating theater organization are often subject of empiricism, leading to far from optimal results. Waiting lists for surgery have always been a societal problem, which governments have been fighting with different management and operational stimulus plans. The current hospital information(More)
Keywords: Metaheuristics VNS Glass container industry Production planning and scheduling Color changeover a b s t r a c t Inspired by a case study, this paper reports a successful application of VNS to the production planning and scheduling problem that arises in the glass container industry. This is a multi-facility production system, where each facility(More)
We propose a general-purpose heuristic approach combining metaheuristics and Mixed Integer Programming to find high quality solutions to the challenging single-and parallel-machine capacitated lotsizing and scheduling problem with sequence-dependent setup times and costs. Commercial solvers fail to solve even medium-sized instances of this NP-hard problem,(More)