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Multi-objective Evolutionary Algorithms to Solve Coverage and Lifetime Optimization Problem in Wireless Sensor Networks

机译:解决无线传感器网络覆盖和生命周期优化问题的多目标进化算法

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Multi-objective optimization problem formulations reflect pragmatic modeling of several real-life complex optimization problems. In many of them, the considered objectives arc competitive with each other and emphasizing only one of them during solution generation and evolution, incurs high probability of producing one sided solution which is unacceptable with respect to other objectives. This paper investigates the concept of boundary search and also explores the application of a special evolutionary operator on a multi-objective optimization problem; Coverage and Lifetime Optimization Problem in Wireless Sensor Network (WSN). The work in this paper explores two competing objectives of WSN;network coverage and network lifetime using two efficient, robust MOEAs. It also digs into the impact of special operators in the multi-objective optimization problems of sensor node's design topology.
机译:多目标优化问题表述反映了一些现实生活中的复杂优化问题的实用模型。在其中许多目标中,考虑的目标相互竞争,并且在解决方案生成和演化过程中仅强调其中一个目标,导致产生单方解决方案的可能性很高,这是其他目标无法接受的。本文研究了边界搜索的概念,并探索了一种特殊的进化算子在多目标优化问题上的应用。无线传感器网络(WSN)中的覆盖范围和生命周期优化问题。本文的工作探索了WSN的两个相互竞争的目标;使用两个高效,强大的MOEA来实现网络覆盖和网络生存期。它还探讨了特殊算子在传感器节点设计拓扑的多目标优化问题中的影响。

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