Modified Intelligent Water Drops Algorithm with Tabu Search (MIWD-TS) for solving Multi-objective Optimization

Multi-objective optimization is widely applied in a number of areas now-a-days. Unfortunately, many combinatorial multi-objective optimization problems are NP-hard. However, it is often unnecessary to have an exact solution. So, heuristic approach can obtain a near-optimal solution in some reasonable time 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 intelligent behavior, effectiveness and efficiency in solving numerous Meta heuristic problems. In this, near optimal solutions are obtained by the actions and reactions that occur among the water drops and the water drops with the riverbeds. Since, this is a constructive approach; it may trap into local optimum. In this paper, IWD algorithm is augmented with Tabu Search to find the optimal values of weighted multi-objective functions. It addresses the issues of exploration and exploitation of candidate solutions in order to provide better optimal solution. The proposed algorithm called the MIWD-TS (Modified Intelligent Water Drops with Tabu Search) algorithm is tested for the composition of Intelligent Test Sheet composition problem which is a multi-objective problem. The experimental results prove that the proposed approach performs well in comparison with other approaches as Random Search and Dynamic programming. Index Terms Intelligent Water Drops, Swarm Intelligence, Meta Heuristic, Weighted Multi-objective optimization, Intelligent Test Sheet ——————————  ——————————