Multi-criterion genetic programming with negative selection for finding Pareto solutions


Abstract

Multi-criterion genetic programming (MGP) is a relatively new approach for a decision making aid and it can be applied to determine the Pareto solutions. This purpose can be obtained by formulation of a multi-criterion optimization problem that can be solved by genetic programming. An improved negative selection procedure to handle constraints in the MGP has been proposed. In the test instance, both a workload of a bottleneck computer and the cost of system are minimized; in contrast, a reliability of the distributed system is maximized.