Shulou(Shulou.com)06/01 Report--

What is the NSGA-II level in multi-objective optimization? for this problem, this article introduces the corresponding analysis and solution in detail, hoping to help more partners who want to solve this problem to find a more simple and feasible method.

| 01 | problem description |

Problem description: suppose there are five types of items, and each category contains four specific items. Now it is required to select one of these five types of items to put in the backpack, so that the total value of the items in the backpack is the largest, the total volume is the smallest, and the total mass is the smallest. (PS: remove the total quality limit of the backpack here). Where P is the value of each item, R is the volume of each item, and C is the mass of each item.

PS: each list of items represents each type of item

02 | algorithm design

In fact, the algorithm design part has not changed much. The detailed design process of the algorithm can refer to the tweet of multi-objective optimization | NSGA-II-based multi-objective 0-1 knapsack problem solving (with matlab code). There are mainly two differences. The first difference is to delete part 2-constraint processing, because there are no constraints in the problem itself. The second difference is that the fitness function changes into three goals, the first goal is the sum of the total value of the item, the second goal is the sum of the total volume of the item, and the third goal is the sum of the total mass of the item. In addition, the editor would like to focus on the meaning of domination.

I think all of you have understood the meaning of domination, but the editor will repeat it here. Ideally, domination can be simply and roughly understood as that all the target values of one solution are better than all the target values of another solution. But this is only an ideal situation. Strictly speaking, domination means that at least one solution is better than the other in one target value, and then in other target values, this solution is not inferior to the other solution. | 03 | experiment result |

We have found a total of 48 Pareto optimal solutions and have drawn them in the coordinate system.

Each of these individuals is shown on the left side of the figure below.

This is the answer to the question about the advance of NSGA-II in multi-objective optimization. I hope the above content can be of some help to you. If you still have a lot of doubts to be solved, you can follow the industry information channel for more related knowledge.

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.