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This paper presents a new generalized particle approach (GPA) to optimally allot the resources and jobs for grid computing (Shuai and Zhao, 2004). The proposed GPA transforms the allocation problem of grid resources and grid jobs into the kinematics and dynamics of massive particles in a force-field. This paper discusses the construction, dynamics and properties of the GPA and corresponding algorithm. The GPA has many advantages in terms of the parallelism, multiobjective optimization, multitype coordination, and the ability to deal with a variety of complex issues, such as the autonomy, personality, congestion, failure of distinct grid facilities. The simulations have shown the effectiveness and suitability of the proposed approach for grid computing.