Minimizing Cost of Redundant Sensor-Systems with an Artificial Immune Algorithm

摘要

Using human immune system mechanisms, an artificial immune algorithm used for minimizing cost of redundant multi-sensor systems is presented in this paper. The search surface for finding the minimal cost of the sensor system while insuring system dependability has many local minima. The heuristic methods must be used to solve the problem. The artificial immune algorithm uses hyper-mutation to search local areas and receptor editing to escape from local minima. It is more suitable than simulated annealing and genetic algorithms for solving this problem. The results produced by the method are compared with results of simulated annealing and genetic algorithm.