Introduction: Optimization and simulation are the most important analytical techniques, and this talk will provide a concise guide to optimization vs. simulation in decision-making. Specifically, we will start with an urban postal service redesign problem in Norway. Due to recent technological advancements, more diversified customer demand, and increasingly harder competition, a strategic reform of urban postal service systems was undertaken in Norway in 2013, called post-in-shop. Decisions need to be made to replace traditional post offices with small-sized postal service counters in retail stores to improve accessibility, operational efficiency, and cost-effectiveness. To solve this problem, a two-stage method is proposed. First, two location models are employed to determine the optimal facility locations, and a simulation model is then built to evaluate the urban postal service system with different location and demand allocation plans under a realistic and stochastic environment. This case study will show both the strengths and the weaknesses of optimization and simulation and how they can be complementarily applied in decision-making. Furthermore, some other application scenarios using combined simulation and optimization methods, e.g., waste management, vaccine distribution, and smart manufacturing, will be briefly introduced.