Safety-based Process Plant Layout Using Genetic Algorithms

Abstract This paper presents a method based on a genetic algorithm for optimizing process plant layout. The relative location of main process units is determined to minimize an annual cost function including the cost of material transfer between process units (piping and pumping costs), land cost, and the expected annual loss resulting from damage to each secondary unit caused by primary accidents occurring in nearby process units. This method is an improvement over previous attempts using genetic algorithms or mathematical programming techniques to optimize plant layout, which neglected pumping costs and included safety issues by evaluating the infringement of predefined safety distances only. In this approach the operating cost of material transfer is included and the likelihood of accidents is taken into account thus providing good practical solutions to the plant layout problem incorporating more realistic cost functions and constraints. In the paper, after discussing the structure of the annual cost function and describing the working logic of the layout generating algorithm, a case study is described to demonstrate the effectiveness of the proposed methodology.

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