To solve the job-shop scheduling optimization problem with robotic cell, several jobs with specific processing operations can be processed on several processing machines, and the handling robot can carry the jobs between the loading/unloading stations and the processing machines. In the real world, due to the uncertainty, especially the processing unit with inventory, the completion time of the job is required in a time window, rather than a specific time point. Therefore, considering the complexity and constraints of the job-shop with robotic cell, the objective is to minimize the total weighted earliness and tardiness. An improved meta-heuristic algorithm is proposed, which combines memetic algorithm with local search technology (variable neighborhood descent). The optimal job processing order and robot handling sequence can be obtained simultaneously. Computational experiments show that the proposed algorithm is more efficient than other algorithms.