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A new interior point algorithm for solving multicriteria optimization problems

Xiaohui Qian, Dongxu Cheng, Yuhui Zheng


Multicriteria optimization problems have many applications in various engineering areas such as bridge-construction designs, energy density, economics, and military strategies. In this paper, we propose a new interior point algorithm to multicriteria optimization problems. Comparing with the commonly used locally convergent algorithms, this new algorithm is globally convergent and reduce the computational cost greatly by making us avoid selecting the initial point via other algorithms.


Multicriteria optimization problems, interior point algorithm, globally convergent.

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