We develop a simulation‐based optimization methodology for the joint design and planning of globalized supply chains (SCs) under minimization objectives for cost and CO2 emissions. The assumptions required for the analytical optimization of such SCs include deterministic lead times, no‐backorder occurrences at central distribution facilities, and powers‐of‐two replenishments of inventories at the SC nodes. The paper aims to investigate whether and how will the decisions that stem from the analytical optimization process change when these assumptions are relaxed. The proposed methodology is employed in a realistic SC structure. The results reveal that (i) the optimal order cycles of the nodes of the SC are not necessarily powers of two, (ii) the central distribution facilities have the option to operate at lower service levels, (iii) the network’s cost and CO2 emissions under optimality are reduced by approximately 0.9%, and (iv) the strategic network design decisions align with those of the analytical solution.
