Efficient Multi-Objective Ant Colony Optimization

Most optimization problems in water resources management require tradeoffs between conflicting objectives.Multi-objective optimization is a growing research area with the aim of finding the Pareto optimal set of solutions which defines the optimal trade-offs. In past studies, the focus has been on developing methods to find Pareto fronts with better diversity and coverage- the issue of objective function evaluation was of secondary importance. However, in water resource applications, objective function evaluations can be computationally very expensive. This leads to our motivation of developing a multi-objective optimization method which not only converges to the optimal Pareto front with improved diversity but also with fewer function evaluations. An efficient multiobjective ant colony optimization method (EMOACO) is proposed and compared against benchmark methods such as NSGA-II, eMOEA and SMPSO. The results demonstrated the capability of EMOACO to converge to the approximate Pareto-optimal with significantly fewer evaluations

کلیدواژه ها:

Multi-objective optimization ، Ant colony optimization ، fast convergence