Solving Robot Path Planning Problem by Using a New Elitist Multi-Objective IWD Algorithm Based on Coefficient of Variation

In this paper, we want to solve multi-objective robot path planning problem. A new elitist multi-objective approach is proposed to determine Pareto front based on coefficient of variation. Intelligent water drops (IWD) algorithm is generalized by this approach and as a new multi-objective IWD algorithm. We call our new algorithm CV-based MO-IWD. It tried to optimize two objectives: length and safety of the path. In the CV-based MO-IWD, we want to discover solutions as close to optimal Pareto solutions as possible and find solutions as diverse as possible in the obtained Pareto front. In this way, coefficient of variation of Pareto front is determined in each objective. Then, appropriate number of heuristic operations (local search in this paper) is calculated and applied for each solution. Implementation results and comparisons with NSGA_II algorithm show the ability of the proposed approach to achieve a near optimal Pareto front with a good diversity, while the number of fitness function calls does not increase. This method is superior because of suitable distribution of heuristic operations.