Investigation of human factors while solving multiple criteria optimization problems in computer network

The aim of this investigation is to analyze a class of multiple criteria optimization problems that are solved by human-computer interaction, using a computer network. A multiple criteria problem is iterated by interactively selecting different weight coefficients of the criteria. Several parallel solution strategies for solving this optimization problem have been developed and analyzed. The experiments have shown the importance of human assistance in solving this multiple criteria problem. New experimental investigations have been carried out with a different number of computers and different strategies where the human factors are analyzed. We have investigated the time necessary for human's training to solve this multiple criteria optimization problem, the dependence of human factors on the strategy of parallel solution and on the number of computers in a computer network.