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TITLE: A Simulation -Based Optimization Platform (SBOP) for discrete logistics systems with applications to workforce scheduling of assembly lines
SPEAKER: Professor Oliver Rose
ABSTRACT:
In this presentation, we focus on solution strategies for scheduling problems in complex assembly lines with workforce constraints. Typical products are airplanes, industrial machines and turbines which are produced by multi-skilled resources in small lots or which are even unique items. This type of production scheduling problem is known as a Multi-Mode Resource-Constrained Multi-Project Scheduling Problems (MMRCMPP) with Activity Splitting. It is a combinatorial problem which is NP-hard.
Existing approaches are far from optimal and provide very rough heuristic results. For our solution approach, we even increase the complexity of the model by using both internal and subcontracted workers with different skills. We use a simulation-based optimization approach to obtain solutions for real-world problems in short runtimes. To that end, we propose a heuristic method for developing production plans with minimized slack, balanced workforce with minimal staff and high resource utilization. As a first step towards a cost optimization we also show how a cost model to evaluate the total cost of production plans can be integrated to our approach. The cost function considers resource cost, opportunity cost (unused resources), subcontracting cost, bonus and penalty payments and assembly overhead cost. We show some solution details including computational results for several production scenarios and a reference implementation of our Simulation-Based Optimization Platform (SBOP).
