Permutation Picture of Graph Combinatorial Optimization Problems
This work addresses a foundational problem in optimization for researchers and practitioners, though it appears incremental as it builds on existing representations.
The paper tackles graph combinatorial optimization problems by proposing a permutation-based representation framework, which includes problems like the travelling salesman and maximum cut, potentially enabling new algorithm designs in neural combinatorial optimization.
This paper proposes a framework that formulates a wide range of graph combinatorial optimization problems using permutation-based representations. These problems include the travelling salesman problem, maximum independent set, maximum cut, and various other related problems. This work potentially opens up new avenues for algorithm design in neural combinatorial optimization, bridging the gap between discrete and continuous optimization techniques.