During the last stage of network reconfiguration after a major blackout， the quick all-round load restoration with the constraints satisfied by stages in proper order is a multi-constraint， non-linear， and integer programming problem. A combinatorial optimization model is developed with the sequencing problem of load pickup taken into account. The effects of pickup sequence are taken into account in the objective function. Multiple constraint conditions such as the frequency， voltage， unit output limit and power flow in different sequences are comprehensively considered. In addition， a method for simplifying transient voltage-dip constraint check is presented. Owing to the rather large optimization range of the to-be-restored loads in the later stage of network reconfiguration， a new adaptive particle swarm optimization algorithm is adopted to solve the model proposed. The adaptive adjustment of parameters is carried out by comparing the quality of individual extrema in the iterative process. Case studies performed on the actual Shandong power system demonstrate that the model proposed can effectively reflect the sequencing problem and the algorithm adopted can satisfy the practical requirements on computation speed.