Multiobjective evacuation routes optimization problem is defined to find out optimal evacuation routes for a group of evacuees under multiple evacuation objectives. For improving the evacuation efficiency, we abstracted the evacuation zone as a superposed potential field network (SPFN), and we presented SPFN-based ACO algorithm (SPFN-ACO) to solve this problem based on the proposed model. In Wuhan Sports Center case, we compared SPFN-ACO algorithm with HMERP-ACO algorithm and traditional ACO algorithm under three evacuation objectives, namely, total evacuation time, total evacuation route length, and cumulative congestion degree. The experimental results show that SPFN-ACO algorithm has a better performance while comparing with HMERP-ACO algorithm and traditional ACO algorithm for solving multi-objective evacuation routes optimization problem.

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Abstract. Node localization is a fundamental and important technology in wireless sensor networks. In this paper, a localization algorithm in wireless sensor networks based on PSO is proposed. Unlike most of the existing location algorithm, the proposed algorithm figures out the rectangular estimation range of unknown node by bounding box algorithm and takes one value as the estimated coordinates of this node, then it has been optimized by PSO, so got the more precise location of unknown nodes. Simulation results show that this optimized algorithm outperforms traditional bounding box on the positioning accuracy and localization error.

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