sKPNSGA-II: Knee point based MOEA with self-adaptive angle for Mission Planning Problems

by   Cristian Ramirez-Atencia, et al.

Real-world and complex problems have usually many objective functions that have to be optimized all at once. Over the last decades, Multi-Objective Evolutionary Algorithms (MOEAs) are designed to solve this kind of problems. Nevertheless, some problems have many objectives which lead to a large number of non-dominated solutions obtained by the optimization algorithms. The large set of non-dominated solutions hinders the selection of the most appropriate solution by the decision maker. This paper presents a new algorithm that has been designed to obtain the most significant solutions from the Pareto Optimal Frontier (POF). This approach is based on the cone-domination applied to MOEA, which can find the knee point solutions. In order to obtain the best cone angle, we propose a hypervolume-distribution metric, which is used to self-adapt the angle during the evolving process. This new algorithm has been applied to the real world application in Unmanned Air Vehicle (UAV) Mission Planning Problem. The experimental results show a significant improvement of the algorithm performance in terms of hypervolume, number of solutions, and also the required number of generations to converge.


page 1

page 9

page 10


Hybrid Adaptive Evolutionary Algorithm for Multi-objective Optimization

The major difficulty in Multi-objective Optimization Evolutionary Algori...

PasMoQAP: A Parallel Asynchronous Memetic Algorithm for solving the Multi-Objective Quadratic Assignment Problem

Multi-Objective Optimization Problems (MOPs) have attracted growing atte...

moGrams: a network-based methodology for visualizing the set of non-dominated solutions in multiobjective optimization

An appropriate visualization of multiobjective non-dominated solutions i...

Multi-objective learner performance-based behavior algorithm with five multi-objective real-world engineering problems

In this work, a new multiobjective optimization algorithm called multiob...

Locating the boundaries of Pareto fronts: A Many-Objective Evolutionary Algorithm Based on Corner Solution Search

In this paper, an evolutionary many-objective optimization algorithm bas...

Trends in the optimal location and sizing of electrical units in smart grids using meta-heuristic algorithms

The development of smart grids has effectively transformed the tradition...

A Parallel MOEA with Criterion-based Selection Applied to the Knapsack Problem

In this paper, we propose a parallel multiobjective evolutionary algorit...

Please sign up or login with your details

Forgot password? Click here to reset