As industry 4.0, IoT and clouding technologies take hold, real-time scheduling and resource allocation solutions by means of proven optimization techniques have a concrete interest and remarkable market opportunities. Concerning logistic and production sectors, some solid well-designed optimization system can be a precious ally to Just-In-Time philosophy at work. Speaking of logistics, it is a fast-growing sector responsible for a significant share of company costs, and its optimization has a major impact on economic rentability and competitiveness. The topic of this thesis is the research of dynamic and flexible scheduling methods for a generic indoor logistic support system. More specifically, the sought methods concern the optimal satisfaction of the expressed material needs of an indoor manufacturing facility, by means of a limited-capacity vehicle fleet.