In this paper we concentrate on Job Shop Scheduling as a representative of constrained combinatorial problems. We introduce a new permutation representation for this problem. Three crossover operators different in tending to preserve the relative order, the absolute order, and the position in...

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...

In dieser Arbeit wurde eine neue Form der Repräsentation von Maschinenbelegungsproblemen für Genetische Algorithmen vorgestellt. Sie behandelt die Maschinenbelegungsplanung in natürlicher Weise durch Reihenfolgenbildung von ausführenden Arbeitsgängen und umgeht dabei dennoch die...

We consider job shop scheduling problems with release and due-dates, as well as various tardiness objectives. To date, no efficient general-purpose heuristics have been developed for these problems. genetic algorithms can be applied almost directly, but come along with apparent weaknesses.

A general model for job shop scheduling is described which applies to static, dynamic and non-deterministic production environments. Next, a Genetic Algorithm is presented which solves the job shop scheduling problem ...

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.

Production scheduling dictates highly constrained mathematical models with complex and often contradicting objectives. Evolutionary algorithms can be formulated almost independently of the detailed shaping of the problems under consideration. As one would expect, a weak formulation of the...