Revisiting surrogate relaxation for the multidimensional knapsack problem

Autor: Trivikram Dokka, Adam N. Letchford, M. Hasan Mansoor

Publikováno v: Operations Research Letters. 50:674-678

The multidimensional knapsack problem (MKP) is a classic problem in combinatorial optimisation. Several authors have proposed to use surrogate relaxation to compute upper bounds for the MKP. In their papers, the surrogate dual is solved heuristically

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2aaeba05a1cc55a0f1bfa7675e44651f
https://doi.org/10.1016/j.orl.2022.10.003

Equilibrium design in an n-player quadratic game

Autor: Trivikram Dokka, Hervé Moulin, Indrajit Ray, Sonali SenGupta

Publikováno v: Dokka, T, Moulin, H, Ray, I & SenGupta, S 2022, ' Equilibrium design in a n-player quadratic game ', Review of Economic Design . https://doi.org/10.1007/s10058-022-00299-2

As in public good provisions, in a public bad situation such as abatement, the non-cooperative interplay of the participants typically results in low levels of quantities (provision or abatement). In a simple class of n-person quadratic games, we sho

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4ad99ed0a2240382dede8ebc0b93540
https://orca.cardiff.ac.uk/id/eprint/149069/1/4a484344-a3bd-42e1-b8ef-b712444cae35.pdf

Automatic generation of algorithms for robust optimisation problems using Grammar-Guided Genetic Programming

Autor: Marc Goerigk, Trivikram Dokka, Martin Hughes

Publikováno v: Hughes, M, Goerigk, M & Dokka, T 2021, ' Automatic generation of algorithms for robust optimisation problems using Grammar-Guided Genetic Programming ', Computers & Operations Research, vol. 133, 105364 . https://doi.org/10.1016/j.cor.2021.105364

We develop algorithms capable of tackling robust black-box optimisation problems, where the number of model runs is limited. When a desired solution cannot be implemented exactly the aim is to find a robust one, where the worst case in an uncertainty

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f0f7f377293a04e423db91a7edfb984
https://pure.qub.ac.uk/en/publications/automatic-generation-of-algorithms-for-robust-optimisation-problems-using-grammarguided-genetic-programming(59397a90-d1cd-48d3-8e62-f87d4c492cf4).html

On the complexity of surrogate and group relaxation for integer linear programs

Autor: Adam N. Letchford, Trivikram Dokka, M. Hasan Mansoor

Publikováno v: Dokka, T, Letchford, A & Mansoor, H 2021, ' On the complexity of surrogate and group relaxation for integer linear programs ', Operations Research Letters, vol. 49, no. 4, pp. 530-534 . https://doi.org/10.1016/j.orl.2021.05.011

Surrogate and group relaxation have been used to compute bounds for various integer linear programming problems. We prove that (a) when only inequalities are surrogated, the surrogate dual is NP -hard, but solvable in pseudo-polynomial time under cer

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c22188e6ed1d3bc7d6e893af251e003
https://pure.qub.ac.uk/en/publications/0f35db21-f374-412f-94ff-93cbc8d41c79

An Efficient Approach to Distributionally Robust Network Capacity Planning

Autor: Trivikram Dokka, Francis Garuba, Marc Goerigk, Peter Jacko

Publikováno v: Lancaster University-Pure

In this paper, we consider a network capacity expansion problem in the context of telecommunication networks, where there is uncertainty associated with the expected traffic demand. We employ a distributionally robust stochastic optimization (DRSO) f

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a7833f27035e0e644be1996dfe1920c
https://eprints.lancs.ac.uk/id/eprint/143195/