Analysis and comparison of five intelligent algorithms for solving maximum cutting problems _ love academic

"Abstract" The maximum cutting problem (max-cut problem) is a typical NP-difficult combinatorial optimization problem. In this paper, 5 kinds of algorithms, such as genetic algorithm, distributed estimation algorithm, Hopfield network method, ant colony algorithm and particle swarm algorithm, are used to solve the maximum cutting problem, and the maximum cutting test data of different scales are tested, the influence of each parameter on the algorithm is studied, and the time complexity and space complexity of each algorithm are compared. The test results show that the five algorithms are different in the execution efficiency, but they can solve the maximum cutting problem better.

"Author" Chen Ning Li Zifen Chen Jinju

Reprint to Love academic: https://www.ixueshu.com/document/4c6a7b654967983a318947a18e7f9386.html

Analysis and comparison of five intelligent algorithms for solving maximum cutting problems _ love academic