One of the worst negative phenomena faced by photovoltaic (PV) array is the operation under the shadow phenomenon, which signicantly affects the generated power. Multiple local maximum power point (MPP) and unique global MPP are generated from the shaded array. Therefore, regular dispersion of the shadow falling on the PV array surface is a vital issue to extract the GMP via reconguration of the shaded modules in the array. This article proposes a recent approach based on Multi-objective grey wolf optimizer (MOGWO) to recongure the shaded PV array optimally. The main objective of the proposed MOGWO is providing the optimal structure for the switching matrix to minimize the row current difference and maximize the output power. The benets of the proposed strategy is performing a dynamic reconguration process which closes to the reality. The proposed method is validated across 99 PV array with six shade patterns. MOGWO schemes results are compared with TCT and modied SuDoKu based on several statistical metrics. The comparison reveals the superiority of MOGWO in tackling the multi-peak issue in the P-V characteristics with harvesting the highest power levels.