Advanced modeling of control and optimization in management science often leads to a computational complexity which cannot be handled by traditional algorithms and computer systems. On this background the paper develops a general approach to combine the power of distribution and parallelism in...

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...

Advanced modeling of control and optimization in management science applications often leads to a computational complexity which cannot be handled by traditional algorithms and computer systems. Since the late 60's this fact (mathematically going by the term of NP-completeness) has been known...