The supply chain's underlying infrastructure affects the efficiency and design of distribution routes. As such infrastructure is associated with substantial capital investments, it is crucial to consider the network design and the location of various facilities. The supply chain network design in this context encompasses two major problem classes; the vehicle routing problem aiming to find optimal routes to serve a set of customers by a fleet of vehicles from various facilities, and the facility location problem aiming to find the optimal location for various facilities. Moreover, these problems are interconnected as the facilities affect the demand fulfillment and the vehicle routing. Such problems are often solved with optimization techniques within the field of Operations Research, which is concerned with the mathematical modeling and algorithmic solution of decision-making problems. In response to changes of the conditions of supply chains, researchers have directed their attention to extending and introducing new problem variants. These extensions and variants address real-life aspects of transportation systems, but also elevate operational complexity, making them harder to solve.

The objective of this thesis is to contribute to the advancement of the field of supply chain network design, by;

1. exploring and identifying opportunities and needs for modeling and solution approaches that address the increased complexity of real-life industrial applications in facility location and distribution systems of goods, and
2. to propose new modeling approaches and solution methods that address such opportunities and needs.

The thesis is based on five appended papers. Paper A presents a network design modeling approach for a reverse supply chain of spent lithium-ion batteries in Sweden and addresses the difficulties in demand estimations.  Paper B is a literature review covering multi-objective location-routing problems; these are strategic models aiming to determine the location of facilities considering aspects of tour planning and multi-stop routes. An annotated review is presented based on the application area of the various models and an analysis of objectives and solution approaches used. Paper C introduces the Hierarchical Multi-Switch Multi-Echelon VRP (HMSME-VRP), which is a new variant of the vehicle routing problem based on a real-life operational problem originating from the policies of a Nordic distribution company. A mixed-integer formulation of the problem is proposed, and its relations to other previously stated VRP variants are analyzed and discussed. As only small instances can be solved using a commercial solver, Paper D presents two different General Variable Neighborhood Search procedures in order to solve realistic-sized instances and instances of real-world size. Paper E extends the HMSME-VRP by considering service times and thus incorporates more real-life aspects. A Hybrid Clustered Ant Colony Optimization algorithm, incorporating two local search schemes based on Variable Neighborhood Descent, is proposed to solve the problem with the increased complexity that the service times entail.