{"ID":2851396,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.21010","arxiv_id":"2510.21010","title":"MOCVXPY: a CVXPY extension for multiobjective optimization","abstract":"MOCVXPY is an open-source Python library for convex vector optimization. It is built on top of CVXPY, a domain-specific language for single-objective convex optimization. MOCVXPY enables practitioners to describe their convex vector optimization problem in an intuitive algebraic language, that closely follows the mathematical formulation. This work presents the main features of MOCVXPY, explains some background of the algorithms it employs to solve the optimization problems, and illustrates its functionality through examples and two real-world applications in finance and energy. MOCVXPY is available at https://github.com/salomonl/mocvxpy under the Apache 2.0 licence, with some documentation and examples.","short_abstract":"MOCVXPY is an open-source Python library for convex vector optimization. It is built on top of CVXPY, a domain-specific language for single-objective convex optimization. MOCVXPY enables practitioners to describe their convex vector optimization problem in an intuitive algebraic language, that closely follows the mathe...","url_abs":"https://arxiv.org/abs/2510.21010","url_pdf":"https://arxiv.org/pdf/2510.21010v1","authors":"[\"Ludovic Salomon\",\"Daniel Dörfler\",\"Andreas Löhne\"]","published":"2025-10-23T21:42:39Z","proceeding":"math.OC","tasks":"[\"math.OC\"]","methods":"[]","has_code":false,"code_links":[{"ID":607899,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2851396,"paper_url":"https://arxiv.org/abs/2510.21010","paper_title":"MOCVXPY: a CVXPY extension for multiobjective optimization","repo_url":"https://github.com/salomonl/mocvxpy","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}