is the initial state of the system, and $C_\tau(\cdot)$ is the cost function at time $\tau$. Figure \[fig: Timeline\] illustrates the dynamics of the problem with the tactical decision timeline: before each period $t$, a network deployment strategy $S(t)$ is decided through relocation decisions $R(t)$ and implemented right before the beginning of period $t$. Then, demand realized and recourse actions are taken in each period $\tau \in T_t$. At the end of periods $T_t$, a network deployment strategy $S(t+1)$ is decided through relocation decisions $R(t+1)$ and implemented right before the beginning of period $t+1$ and the process repeats.

Operations Cost Approximation and Synchronization Modeling \[under op\]
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Once decisions on capacity deployment are set for a given period $t$, they strongly impact the quality of operations performed by couriers and riders. More specifically, capacity at each location impacts the number and costs of detour and perturb the synchronisation of the operations between couriers and riders at each location. Accordingly, the surrounding objective of integrating routing operations is to evaluate the performance of the capacity deployment in minimizing the detours due to an underestimation of the capacity needs and in guaranteeing the synchronisation of the operations between couriers and riders at 