Discrete Optimization using String Encodings for the Synthesis of Complete Chemical Processes

The use of discrete programming techniques for the synthesis of process flowsheets in chemical engineering is a well established approach. Recently, improvements in the basic algorithms have been made to deal with the generation of complete processes, including heat exchange networks and processes with reactors, absorbers, flash units, etc. This paper describes a new approach to the use of dynamic programming using string encodings both for subproblem definition and for solution description. These encodings, combined with the use of dynamic hash tables, are used to implement a dynamic programming based optimization algorithm for the synthesis of chemical processes. The implementation shows an increase in both efficiency and usefulness.

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