Dynamic Clustering is an efficient topology management approach for sensor networks. Observing the fact that the clustering has tight relations with inter-cluster routing problem, we propose a hybrid clustering and routing protocol (HCR) that considers both the cluster head selection and routing discovery problems. Random backoff and gradient routing strategies are used to achieve our design goals with low overhead. Considering the limited transmission range bounded by the hardware, the clustered network generated by HCR is ensured to be connected. Simulation results demonstrate that our proposed strategies ensure the connectivity of the network and improve the energy efficiency for data transmission.

A new method to solve multiohjective optimization problems (MOP'S), called the interactive step trade-off method (ISTM), is proposed here. With the help of an auxiliary problem A P (c '-'). the preferred solutions of MOP's will he found on their efficient solution faces in ISTM. Using local trade-off information presented hy the analyst, the decisionmaker (DM) makes decisions step by step, which heuristically directs the analyst to look for efficient solutions of MOP's, along preference directions, in proper step sizes, until the preferred solutions are found. The interaction in the method is practical, clear, and easy to understand. The method may he used in the design of decision support systems in such fields as the production management of industrial enterprises.

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