When designing supply chains, firms are often faced with the competing demands of improved customer service and reduced cost. We extend a cost-based location-inventory model (Shen et al. 2003) to include a customer service element and develop practical methods for quick and meaningful evaluation of cost/service trade-offs. Service is measured by the fraction of all demands that are located within an exogenously specified distance of the assigned distribution center. The nonlinear model simultaneously determines distribution center locations and the assignment of demand nodes to distribution centers to optimize the cost and service objectives. We use a weighting method to find all supported points on the trade-off curve. We also propose a heuristic solution approach based on genetic algorithms that can generate optimal or close-to-optimal solutions in a much shorter time compared to the weighting method. Our results suggest that significant service improvements can be achieved relative to the minimum cost solution at a relatively small incremental cost.