Multi-objective evolutionary algorithms to solve coverage and lifetime optimization problem in wireless sensor networks
Abstract
Multi-objective optimization problem formulations reflect pragmatic modeling of several real-life complex optimization problems. In many of them, the considered objectives are 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. © 2010 Springer-Verlag.
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Recommended Citation
Chaudhuri, K., & Dasgupta, D. (2010). Multi-objective evolutionary algorithms to solve coverage and lifetime optimization problem in wireless sensor networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6466 LNCS, 514-522. https://doi.org/10.1007/978-3-642-17563-3_60
