Abstract
Abstract This paper presents a hybridizing meta-heuristic approach to address large-scale multi-floor process plant layout problems, based on the mixed integer linear programming (MILP) model introduced by Ejeh et al. (2018a). The proposed method integrates expert knowledge with Simulated Annealing and commercial optimization solver to seek for better solutions in an iterative manner. The optimization process is realized in four steps. Firstly, expert knowledge drawn from engineering practices are applied to reduce the searching space of possible equipment layout. Secondly, a preliminary process layout is generated stochastically which gives deterministic floor information for the equipment. Thirdly, detailed process layout is obtained by commercial optimization solver. Fourthly, the second and third step are repeated under a Simulated Annealing framework, which compares the cost of each possible layout candidate and selects the most competitive. Three examples are illustrated to verify the efficacy of the proposed method. The result shows that the proposed optimization approach successfully achieves good quality multi-floor layout solutions with satisfactory computational requirement.
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