We discuss strategic, multi-site design and planning problems on their own, and their combination in models arising from operational planning models extended by design features, but also by adding operational features to design problems. Typical strategic planning aspects in the chemical, pharmaceutical, and food industry, but also parts of the metals industry, are the start-tip of new units and the shut-down of existing units or whole production sites to be purchased or sold, out-sourcing or in-sourcing decisions, the design of production facilities, distribution networks, customer or product portfolios, and the financial design of global supply chains with variable transfer prices. Mixed integer programming is the basis to solve planning problems. Usually. in operational planning all functions are linear. In contrast. strategic or design problems may involve nonlinear terms. We favor combined planning models and their implementation in algebraic modeling languages If the problem size or structure exceeds the capabilities of modern solvers, tailor-made solution strategies are recommended including decomposition techniques (rolling time approaches, column generation and Branch&Price) or hybrid techniques in which constructive heuristics and local search methods are coupled with exact algorithms generating feasible points and tight bounds. As a technical innovation we. here present new approaches to improve Big-M formulations dynamically by solving a sequence of auxiliary problems, or replacing Big-M for mulations by branching on SOS-1 sets.