ABSTRACT
This chapter describes a new proposed algorithm which is used inspired from swarm intelligence, called the Brain Storm Optimization (BSO) algorithm. The algorithm is used with some of the normalization methods not only to solve the coverage problem but also the connectivity problem. BSO is treated as a multiobjective solution to the coverage and connectivity problems of wireless sensor network (WSN). A WSN is formed through different steps including the deployment, self-organizing, operation, and maintenance. The chapter talks about genetic algorithms (GAs) which is consist of four steps: initialization, selection process, genetic operators such as crossover and mutation, and termination process. Brainstorming process is translated to formal algorithmic steps to be suitable for optimization problems including the generation process, clustering process, and mutation and selector operators. A simple mutation operator is to randomly change some of the genes of the newly generated child to expand the search space.
