Grossone Methodology for Lexicographic Mixed-Integer Linear Programming Problems-Reference-Cited by-同舟云学术

Grossone Methodology for Lexicographic Mixed-Integer Linear Programming Problems

Published:2020 Issue: Volume: Page:337-345
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Cococcioni Marco^ORCID,Cudazzo Alessandro^ORCID,Pappalardo Massimo^ORCID,Sergeyev Yaroslav D.^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-40616-5_28

Reference16 articles.

1. Cococcioni, M., Cudazzo, A., Pappalardo, M., Sergeyev, Y.D.: Solving the lexicographic mixed-integer linear programming problem using branch-and-bound and Grossone methodology. Comm. Nonlinear Sci. Numer. Simul., Submitted

2. Cococcioni, M., Pappalardo, M., Sergeyev, Y.D.: Lexicographic multi-objective linear programming using grossone methodology: theory and algorithm. Appl. Math. Comput. 318, 298–311 (2018)

3. De Leone, R., Fasano, G., Sergeyev, Y.D.: Planar methods and grossone for the conjugate gradient breakdown in nonlinear programming. Comput. Optim. Appl. 71, 73–93 (2018)

4. Fiaschi, L., Cococcioni, M.: Non-archimedean game theory: a numerical approach. Submitted

5. Fiaschi, L., Cococcioni, M.: Numerical asymptotic results in game theory using Sergeyev’s infinity computing. Int. J. Unconventional Comput. 14, 1–25 (2018)

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