Evaluates multi-objective optimisation in prefabricated construction, suggesting improved early-stage decisions.
Building Information Modelling (BIM) workflows for prefabricated construction lack mechanisms that generate and compare alternative component configurations directly from a design model. Existing approaches define the optimisation search space manually and outside the model, address only one or two criteria, and treat the Work Breakdown Structure (WBS) as a post-design planning tool. This paper reinterprets the WBS as a generative decomposition mechanism. A WBS Engine decomposes the geometry of an existing BIM model into prefabricated subsystems before design decisions are fixed, producing the search space for optimisation without manual parametrisation. A Scenario Evaluator queries a database of 47 prefabricated components, and NSGA-II evaluates 60 configurations against four objectives. These are total cost, embodied carbon, assembly factor and number of lorry trips. Applied to a residential case study implemented in Dynamo, the prototype identified 16 non-dominated solutions. The best compromise configuration achieved a total cost of £150,444.01, 127,731.00 kgCO2e, an assembly factor of 0.190 and 10 lorry trips. Wall module size accounted for 17.4% of cost variation, while floor module size governed assembly complexity. The findings show that BIM-WBS integration with multi-objective optimisation supports informed early-stage decisions in industrialised construction.
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Abrishami et al. (2026) studied this question.
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