Publicação
On the complexity of a linear programming predictor-corrector algorithm using the Two Norm Neighborhood
| Resumo: | In this work the complexity of a feasible variant of a Linear Programming Predictor-Corrector algorithm specialized for transportation and assignment problems is explored. A O(n| log (ϵ) | ) iteration complexity was achieved by proving that the step size computed by the studied algorithm is bounded at each iteration by θ(4-3θ)(1-θ)2n, where θ∈ [ 0, 1 [. Therefore, allowing to conclude that the analyzed Predictor-Corrector algorithm that uses the 2-norm neighborhood has polynomial iteration complexity and is Q-linearly convergent. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG |
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| Autores principais: | Almeida, Regina De |
| Outros Autores: | Teixeira, Ana Paula |
| Assunto: | Feasible predictor-corrector algorithm Polynomial complexity Transportation and assignment problems |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | documento de conferência |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade de Trás-os-Montes e Alto Douro |
| Idioma: | inglês |
| Origem: | Repositório da UTAD |
| Resumo: | In this work the complexity of a feasible variant of a Linear Programming Predictor-Corrector algorithm specialized for transportation and assignment problems is explored. A O(n| log (ϵ) | ) iteration complexity was achieved by proving that the step size computed by the studied algorithm is bounded at each iteration by θ(4-3θ)(1-θ)2n, where θ∈ [ 0, 1 [. Therefore, allowing to conclude that the analyzed Predictor-Corrector algorithm that uses the 2-norm neighborhood has polynomial iteration complexity and is Q-linearly convergent. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG |
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