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The introduction of mobile elements has created a new dimension to reduce and balance energy consumption in wireless sensor networks, however, data collection latency may become higher. Thus the scheduling of mobile elements, i.e., how they traverse through the sensing field and when they collect data from which sensor, is of ultimate importance and has attracted increasing attention from the research community. Formulated as the Traveling Salesman Problem with Neighborhoods (TSPN) and due to its NP-hardness, so far only approximation and heuristic algorithms have appeared in the literature, but the former only have theoretical value now due to their large approximation factors. In this paper, following a progressive optimization approach, we propose a combine-skip-substitute (css) scheme, which is shown to outperform the best known heuristic algorithm. Besides the correctness and complexity analysis of the proposed scheme, we also show its performance and potentials for further extension through extensive simulation results.