Note: Because it was not mentioned in the previous article that dimensionality reduction is not used in Gurobi. So reposting here.
Comparison results of our optimization algorithm with Gurobi (commercial software) and Scip:
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Our algorithm has obvious speed advantages when there are few orders.
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When solving high-dimensional spaces, our speed and efficiency are higher than gurobi.
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When comparing with Gurobi, no targeted dimensionality reduction processing was performed.
Our features:
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Generally, an important means of solving problems in integer linear programming (ILP) is dimensionality reduction. Some problems require targeted dimensionality reduction.
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Our algorithm uses a spatial search algorithm. No dimensionality reduction is required. Therefore, it will have advantages when dealing with high-dimensional problems.
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More importantly, we can solve nonlinear problems even when explicit formulas cannot be written.
We need engineers who can help transform problems in business scenarios, convert business requirements into mathematical models, and use appropriate tools to solve them.
More importantly, we hope to use tools to improve the efficiency of economic and social operations. Come work together to protect the environment, protect the planet, protect our children, and their children.
I hope you succeed, and I hope you protect and save our planet, for your children, and for all children in the future.
The total funding is 470 million yuan! Fudan University was approved to build a national integrated circuit industry-education innovation platform
For other links, please see the following articles:
https://zhuanlan.zhihu.com/p/68669044
Note: WeChat official account is a closed system and cannot directly embed links to other articles, which is very troublesome.
Machine-translated from the Chinese original Vrp优化算法和Gurobi，Scip的比较 (published 2019-06-12). WeChat original ↗