A Mathematical Model for Dynamic Project Scheduling Problem and Reactive Scheduling Implementation

Abstract

In today's real-life implementations, projects are executed under uncertainty in a dynamic environment. In addition to resource constraints, the baseline schedule is affected due to the unpredictability of the dynamic environment. Uncertainty-based dynamic events experienced during project execution may change the baseline schedule partially or substantially and require projects' rescheduling. In this study, a mixed-integer linear programming model is proposed for the dynamic resource-constrained project scheduling problem. Three dynamic situation scenarios are solved with the proposed model, including machine breakdown, worker sickness, and electricity power cut. Finally, generated reactive schedules are completed later than the baseline schedule.

Dynamic multi-mode resource-constrained multi-project scheduling problem with weighted earliness and tardiness: a real-life boutique furniture implementation

“…They formulated a mixed-integer linear programming (MILP) model that minimized total tardiness and proposed a dynamic approach to solve modified MILP models to revise the schedule for new project arrivals, workload balancing, and precedence changes. Ruhlusaraç and Çalışkan (2020) proposed a mathematical model for the dynamic project scheduling problem and its reactive scheduling implementations. Chakrabortty, Rahman and Ryan (2020) reviewed the RCPSP under dynamic environments with stochastic activity durations, unstable resource availability, and time-varying resource demands.…”