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In this paper, an optimisation-based approach to obtain safe multi-oor process plant layout designs using the Domino Hazard Index (a sub-index of the Integrated Inherent Safety Index) is presented. A mixed integer linear programming (MILP) model is proposed to obtain the economically optimal multi-oor layout design considering connection by pipes, horizontal and vertical pumping of process uids, purchase of land, xed and area-dependent construction of oors, the nancial risk associated with hazardous events and their escalation potential, and the installation of passive protection devices. Hazardous events such as pool res, jet res, ash res, reballs and blast waves resulting from explosions are considered using a novel and more realistic estimation of safety distances between equipment items. A bi-objective optimisation problem is also considered, minimising the layout costs and the total domino hazard index values for the plant, adopting the -constraint method. The proposed model is then applied to an 11-unit case study susceptible to each of these hazardous events, obtaining results with the optimal layout and protection device congurations in a relatively short amount of time.

In this work, a new mixed integer linear programming (MILP) model is proposed for the multi-oor process plant layout problem with additional considerations. Multi-oor process plant layout determines the spatial arrangement of process plant units considering their connectivity amongst other factors and aects the cost of constructing the plant, the ease of plant operation and expansion, general safety levels within the plant and its neighbouring environment, as well as operational costs. Over the past years, mathematical programming models have been developed to describe the layout problem considering connectivity costs, pumping costs, installation of safety devices, and piping, in single and multiple oors. Features such the representation of irregularly shaped items, tall equipment spanning multiple oors and others have been successfully modelled. This work builds on such past considerations with additional features that allow multi-oor equipment items extend above the maximum potential number of oors, and the selection of an available number of oors less than the maximum number required by any equipment item. Integer cuts are also developed for the proposed model to enhance its eciency. The performance and limitations of the proposed model are demonstrated with industry-relevant case studies of up to 25 units, and results show a potential cost savings when compared to existing models with additional computational benets of the integer cuts in all of the cases explored.