The application of adaptive optimization strategies to scheduling in manufacturing systems has recently become a research topic of broad interest. Population based approaches to scheduling predominantly treat static data models, whereas real-world scheduling tends to be a dynamic problem. This...

A frequently observed difficulty in the application of genetic algorithms to the domain of optimization ariscs from premature convergence. In order to preserve genotype diversity we develop a new model of auto-adaptive behavior for individuals. In this model a population member is an active...

The population of parallel genetic algorithms (PGAs) can easily be split up to match the needs of a coarse grained parallelism. A cluster of interconnected workstations, seen as an MIMD-architecture, is the chosen hardware to express this kind of parallelism. A PGA implementation, as any other...

This paper adresses job tardiness for non deterministic job shop scheduling. A comparative study shows that a GA consistently outperforms different priority rules regardless of the workload and the objective pursued.