Optimization of the tactical allocation of resource capacities at an academic animal hospital

This thesis seeks to improve the patient flow at an academic animal hospital. The research focusses on the main obstructions with identified root causes that can be traced back to capacity management-related problems. Here, we make a distinction between problems related to the allocation of resources (the design of the production planning) that causes over- and under capacity, extremely unbalanced workload and mismatches between the supply of and demand for resources, and problems related to the patient appointment planning processes that results in short-term inefficiencies, unrealistic schedules, unnecessary long waiting times both at home and in the hospital, and many obstructions of the patient flow. Through simulation based optimization, the exploitation of Variability buffering and exploration of what-if scenarios, we find ways to substantially save on capacity while maintaining acceptable performances on other Key Performance Indicators. We provide more insights in how performances may be steered and how the allocation of resources can be handled.