Repair algorithms and penalty functions to handling constraints in an evolutionary scheduling

Abstract

Ecosystems are directly and negatively affected by many industrial risky activities such as the oil transportation and exploitation. It is therefore important that oil companies carry out a correct maintenance of their oil fields. In this work we implement in our previously proposed evolutionary optimization tool (called PAE) a set of constraint-handling techniques to solve a constrained version of the maintenance problem. The results and comparisons demonstrated that the proposed repair algorithm required less computational effort (evaluations) with the same quality of solutions for the set of instances used.