Detecting a randomly moving COVID-19 using weight Tchebycheff optimization technique

Abstract

This paper completely characterizes the search for randomly moving COVID-19 among a finite set of different states (cells). A search effort at each fixed number of time intervals is a random variable with a given distribution. Both of probability of detecting the COVID-19 in a certain state j at a certain time i and the detection functions are supposed to be known to the searcher or robot. We seek for the optimal distribution of the effort to deduce an explicit formula for the optimality distribution of the random variable effort using weighted Tchebycheff optimization technique. We find the necessary conditions for the optimal search technique. An algorithm is constructed for generated weighted Tchebycheff optimization technique. The effectiveness of these techniques is illustrated by numerical results which indicate that the proposed techniques are promising.