Proactive project scheduling in an R&D department a bi-objective genetic algorithm

In this paper, we present part of a study on stochastic, dynamic project scheduling in an R&D Department of a leading home appliances company in Turkey. The problem under consideration is the preemptive resource constrained multi-project scheduling problem with generalized precedence relations in a stochastic and dynamic environment. The model consists of three phases. Phase I of the model provides a systematic approach to assess uncertainty resulting in activity deviation distributions. In Phase II, proactive project scheduling is accomplished through two different scheduling approaches, which employ a bi-objective genetic algorithm. Phase III is the reactive project scheduling phase aiming at rescheduling the disrupted project activities. Here, we will limit our presentation to Phase II - the proactive project scheduling phase. The procedure is demonstrated through an implementation with real data covering 37 R&D projects. Computational study is performed to compare the two different scheduling approaches called single and multi-project scheduling approaches, as well as two different chromosome evaluation heuristics. Results are presented and discussed.