| In this research, we propose approaches to model and solve the joint problem of facility location, inventory allocation, and capacity investment when demand is stochastic. We incorporate practical attributes of finite and constrained inventory levels, a complex and variable repair process, and long-term labor capacity planning from multiple labor sources. The objective of our work is to support policy- and decision-makers with a computationally efficient and effective modeling framework in an iterative decision process environment. Extensive research has been established in the fields of facility location theory, inventory theory, and queueing theory; yet research that explores the intersection of these fields is limited. Performance at a tactical level is often an output of strategic decisions. However, attempts to incorporate tactical considerations may create models that are computationally intractable. Our framework unites the strategic and tactical considerations of the problem and shows improved decisions and performance to models that do not incorporate tactical considerations. |
