Mobile grid computing is aimed at making grid services available and accessible anytime anywhere from mobile device; at the same time, grid users can exploit the limited resources of mobile devices. This paper proposes simultaneous optimization of application utility and consumed energy in mobile grid. The paper provides a comprehensive utility function, which optimizes both the application level satisfaction such as execution success ratio and the system level requirements such as high resource utilization. The utility function models various aspects of job, application and system. The goal of maximizing the utility is achieved by decomposing the problem into a sequence of sub-problems that are then solved using the NUM optimization framework. The proposed price-based iterative algorithms enable the sub-problems to be processed in parallel. The simulations and analysis are given to study the performance of the algorithm.