Multi-objective optimization of lean-based repetitive scheduling using batch and pull production

Repetitive scheduling (RS) using conventional methods suffers from many drawbacks due to forced resource continuity assumptions that increase time and cost. Moreover, it leads to an increased work-in-progress (WIP) inventory of units as a result of the unit's idle time between successive activities. Interruption-based RS techniques were introduced to reduce project duration, however, they didn't address WIP inventory and its repercussions. Accordingly, this research developed a new lean-driven Pull-Batch-based Repetitive Scheduling (PBRS) technique that utilizes batch- and pull-production lean concepts to reduce WIP, time, and cost. It has a built-in multi-objective optimization algorithm to determine the optimum number of batches and crews that minimizes time and cost considering the counter impact of resource and unit idleness. A real case study was used to evaluate the performance of the new PBRS technique against the existing ones. The results demonstrated the PBRS superiority and the optimization model's capability to generate optimum schedules. •A new PBRS model that integrates both batch and pull production lean concepts with repetitive scheduling is developed.•Mathematical formulations are developed to compute the impact of batching and pulling on project duration, cost, and WIP.•A new multi-objective optimization model is developed to minimize time, cost, and WIP associated with the new PBRS model.•A new visualizion of WIP in terms of construction cycle time and number of working units is developed.