Enriched Intelligent Water Drops (EIWD) Algorithm with Genetic Operator to Solve Weighted Multi-Objective Optimization Problems

摘要

The multiple criteria nature of most real world problems has boosted research on multi-objective algorithms that can tackle such problems effectively, with the smallest possible computational burden. Intelligent Water Drops algorithm (IWD) a new swarm-based optimization algorithm has attracted the interest of researchers due to its simplicity, effectiveness and efficiency in solving numerous single-objective optimization problems. In this near optimal or optimal paths are obtained by the actions and reactions that occur among the water drops and the water drops with the riverbeds. The algorithm may trap into local optimum. In this paper, IWD algorithm is augmented with genetic operators to find the optimal values of weighted multi-objective functions. It addresses the issues of exploration of exploitation of candidate solutions in order to provide better optimal solution. The proposed algorithm called the E1WD (Enriched Intelligent Water Drops) algorithm is tested for the composition of Intelligent Test Sheet composition problem which is multi-objective problem. The experimental results are satisfactory, which encourage further researches in this regard.