The biobjective minimum‐cost perfect matching problem and Chinese postman problem

Author:

Pozo Miguel A.12ORCID,Puerto Justo12ORCID,Roldán Ignacio2ORCID

Affiliation:

1. Department of Statistics and Operational Research University of Seville Sevilla Spain c/ Tarfia, s/n. 41012

2. Institute of Mathematics of the University of Seville Sevilla Spain Edificio Celestino Mutis, Primera planta, Campus de Reina Mercedes. Avda. Reina Mercedes, s/n, 41012.

Abstract

AbstractIn this paper, we address the biobjective versions of the perfect matching problem (PMP) and the Chinese postman problem (CPP). Both problems are solved by means of integer formulations or separating blossom inequalities, exploiting the PMP relationship with the CPP. In both cases, we first find the set of supported nondominated solutions and then we use them to obtain the nonsupported ones. The set of supported nondominated solutions are obtained solving scalarized integer formulations. To obtain the sets of nonsupported solutions, we resort to solving lexicographic problems based on adding additional linear constraints to the original problems. For this reason, we also characterize the combinatorial structure of the PMP vertices with one or two additional constraints. We also investigate when it is possible to use the PMP to solve CPP in the biobjective case. We report computational experiments comparing the different approaches and formulations based on different types of graphs with up to 700 nodes.

Funder

Ministerio de Ciencia e Innovación

Agencia Estatal de Investigación

Federación Española de Enfermedades Raras

Junta de Andalucía

European Social Fund

Publisher

Wiley

Subject

Management of Technology and Innovation,Management Science and Operations Research,Strategy and Management,Computer Science Applications,Business and International Management

Reference27 articles.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Managing ESG ratings disagreement in sustainable portfolio selection;Computers & Operations Research;2024-10

2. An extended ε‐constraint method for a bi‐objective assortment optimization problem;International Transactions in Operational Research;2023-12-28

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