Computer Science
5 years ago

New algorithm discovers numerous optimal solutions for complex problems.

Searching for Local Pareto Optimal Solutions: A Case Study on Polygon-Based Problems
Yiping Liu, Hisao Ishibuchi, Yusuke Nojima, Naoki Masuyama, Yuyan Han

Paper Summary

Local Pareto optimal solutions can be useful in solving complex problems with multiple objectives. A modified evolutionary algorithm called DNEA-L was developed to find these solutions in polygon-based problems. The algorithm was successful in discovering a variety of local Pareto optimal solutions efficiently.

Related papers

Theme background image
Computer Science
8 years ago

Variable neighborhood search outperforms local search in optimization challenges.

Swarm Intelligence
Constraint Optimization
Robotics Coordination
Theme background image
Engineering
8 years ago

New Study Reveals Faster Scheduling Algorithms for Parallel Machines

Scheduling Problems
Robotics Coordination
Cutting Optimization
Theme background image
Computer Science
6 years ago

New algorithm outperforms others, finding new best solutions for complex problems.

Swarm Intelligence
Routing Problem
Genetic Programming