Using Integrated Simulation-Optimization to Optimize Staffing Decisions in a Service Supply Chain

  The purpose of this research is to address the problem of staffing skilled personnel in a service setting where personnel are drawn from an outsourcing firm and where uncertainty in resource availability is explicitly considered. To achieve this objective, we design and implement a new simulation-optimisation algorithm by combining a scatter search metaheuristic with Monte Carlo simulation. Through a real-life case study and a comprehensive computational experiment, this paper shows that the solution quality provided by our simulation-optimisation framework is superior to the deterministic solution based on point estimates. The framework explicitly addresses uncertainty results in a staff sourcing strategy that is robust and less prone to be impacted by changes in resource availability. Effective implementation of such a framework in outsourcing context requires well-coordinated information sharing and integrated decision-making between the supply chain partners.