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The Process Programming Basics: Priorities, Heuristic or Genetic Algorithms? This paper analyzes methods to optimize process programming, starting with the heuristic algorithms, then reviewing the current method previously advanced by the authors, the quantitative priorities, and finally approaches the problem with an innovative and promissory concept: the genetic algorithms and the “total costs and risks” optimization criterion, which is an alternative to both optimization with constraints and optimization with Lagrange multipliers. This new method emulates natural systems, thus borrowing from their robustness and adaptability. The method proves particularly useful in a turbulent and changing environment, requiring a realistic simulation model and also parallel processing in a high power computing grid. |
