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              <p>In this paper we consider Maximal Lifetime Coverage Prob- lem in Wireless Sensor Networks which is formulated as a scheduling problem related to activity of sensors equipped at battery units and monitoring a two-dimensional space in time. The problem is known as an NP-hard and to solve it we propose two heuristics which use specific knowledge about the problem. The first one is proposed by us stochastic greedy algorithm and the second one is metaheuristic known as Simu- lated Annealing. The performance of both algorithms is verified by a number of numerical experiments. Comparison of the results show that while both algorithms provide results of similar quality, but greedy algo- rithm is slightly better in the sense of computational time complexity.</p>
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