Data‐driven out‐of‐order model for synchronized planning, scheduling, and execution in modular construction fit‐out management

Abstract

Fit‐out operations in modular construction exhibit unique features, such as limited room space and diversly distributed operations in the building. These features pose significant challenges to planning, scheduling, and execution (PSE) of fit‐out activities due to operational parallelism, distributional diversity, and narrower constrained time window in modular construction. Hence, logistics‐operation and multi‐operations synchronizations in a real‐time manner are crucial for PSE of modular construction fit‐out management. With the support of cutting‐edge information technologies, the real‐time data inside the generated digital twins can simplify online optimization models and convert stochastic factors into deterministic parameters. This paper formulates a novel real‐time data‐driven out‐of‐order (OoO) model for synchronized PSE in modular construction fit‐out management. Drawing inspiration from OoO mechanism in Central Processing Unit (CPU), a real‐time data‐driven and rolling‐horizon‐based OoO model is proposed for PSE of modular construction fit‐out, employing a forward heuristic algorithm for solution. Time–space–state data from digital twins are updated to facilitate dynamic decision‐making of managers. Through stochastic computational experiments, we demonstrate the effectiveness of OoO model in optimizing project metrics and the improved resilience in uncertain environments.