Minimizing recovery cost of network optimization problems

We propose a two-stage recoverable robustness approach that minimizes the recovery cost. In many applications, once uncertainty ξ $$ \xi is revealed, it can be more important to recover solution x {x}^{\xi } which as similar possible nominal n o m {x}^{nom} than minimize objective value of . This for example occurs when implemented on regular basis or revealed late. define proactive problem weighted costs over discrete set scenarios while ensuring optimality model cost scenario by distance between first-stage and second-stage recovered this scenario. show two different distances d v l {d}_{val} s t r u c {d}_{struct}