A constraint programming approach for scheduling repetitive projects with atypical activities considering soft logic

Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems.