Heuristic framework for the resource constrained multi-project scheduling problem

Real world scheduling problems can be affected by diverse and conflicting goals. Some scheduling problems are bounded with limited resources and represent a considerable challenge to planners. When multiple projects are involved, scheduling problems become even more complex and difficult to resolve. Because of the combinatory explosions and unrealistic assumptions, traditional management sciences techniques such as PERT, CPM, and a host of similar project schedulers are very limited to special cases of scheduling problems. Recent developments of artificial intelligence (AI) and knowledge engineering techniques have made the development of expert systems which can be driven by scheduling heuristics to resolve problems associated with the traditional optimization techniques by giving ‘better’ rather than ‘best’ solutions. This paper presents the conceptual framework and development strategy for an expert system in multi-project scheduling domains. This paper will also present a practical application of the scheduling system.