A reliable provision of materials in production is a prerequisite for the timely fulfillment of customer orders. Especially in flexible job shop scheduling problems (FJSPs), it is essential to coordinate the use of intralogistics resources in a way that avoids bottlenecks in the production process. In this context, traceability systems offer promising opportunities to record the current location and status of load carriers and suitable means of transport. Established production scheduling approaches rarely consider dynamic information from in-house logistics systems. Consequently, this paper presents an adaptive production planning and control system which integrates the efficient distribution of intralogistics resources into the scheduling process. A model predictive controller using a genetic algorithm is implemented to generate coordinated production and logistics schedules based on process data in a real production environment. By this, a higher utilization of load carriers and means of transport is achieved leading to lower number and costs of required intralogistics resources compared to a planning scenario in which they are neglected.
Herrmann et al. (2026) studied this question.