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Demand side management is one of the most effective methods to control the usage of energy so as to achieve reliability and sustainability in the smart grid. Conventional methods for generating the management scheme are generally based on one objective, which represents only the requirements of energy suppliers or only the energy consumers. In this paper, a multiobjective genetic algorithm (GA) is...
Research into maximizing the network lifetime is one of the most significant and challenging areas in wireless sensor networks (WSNs). By arranging sensors and sinks to realize target coverage and network connectivity respectively, an efficient schedule of sensors and sinks can prolong the network lifetime. However, the arrangements of sensors and sinks correlate with each other because each sensor...
Real coded genetic algorithms (RCGAs) have been widely studied and applied to deal with continuous optimization problems for years. However, how to improve the degree of accuracy so as to produce high quality solutions is still one of the main difficulties that RCGAs face with. This paper proposes a novel mutation scheme for RCGAs. The mutation operator is defined as a linear map in the space of chromosomes...
Maximizing the lifetime of a sensor network by scheduling operations of sensors is an effective way to construct energy efficient wireless sensor networks. After the random deployment of sensors in the target area, the problem of finding the largest number of disjoint sets of sensors, with every set being able to completely cover the target area, is nondeterministic polynomial-complete. This paper...
The SET k-cover problem is an NP-complete combinatorial optimization problem, which is derived from constructing energy efficient wireless sensor networks (WSNs). The goal of the problem is to find a way to divide sensors into disjoint cover sets, with every cover set being able to fully cover an area and the number of cover sets maximized. Instead of using deterministic algorithms or simple genetic...
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