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The aim of this paper is to develop improved polynomial-time approximation algorithms belonging to the family of the fully polynomial time approximation schemes (FPTAS) for a group of scheduling problems. In particular, the new technique provides a positive answer to a question posed more than three decades ago by Gens and Levner [G.V. Gens and E.V. Levner, Discrete Appl. Math. 3 (1981) 313–318]: “Can an epsilon-approximation algorithm be found for the minimization version of the job-sequencing-with-deadlines problem running with the same complexity as the algorithms for the maximization form of the problem?”
Elalouf, Amir 1 ; Levner, Eugene 2
@article{RO_2016__50_4-5_681_0, author = {Elalouf, Amir and Levner, Eugene}, title = {Improving the solution complexity of the scheduling problem with deadlines: {A} general technique}, journal = {RAIRO - Operations Research - Recherche Op\'erationnelle}, pages = {681--687}, publisher = {EDP-Sciences}, volume = {50}, number = {4-5}, year = {2016}, doi = {10.1051/ro/2016021}, zbl = {1357.90052}, mrnumber = {3570524}, language = {en}, url = {http://geodesic.mathdoc.fr/articles/10.1051/ro/2016021/} }
TY - JOUR AU - Elalouf, Amir AU - Levner, Eugene TI - Improving the solution complexity of the scheduling problem with deadlines: A general technique JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2016 SP - 681 EP - 687 VL - 50 IS - 4-5 PB - EDP-Sciences UR - http://geodesic.mathdoc.fr/articles/10.1051/ro/2016021/ DO - 10.1051/ro/2016021 LA - en ID - RO_2016__50_4-5_681_0 ER -
%0 Journal Article %A Elalouf, Amir %A Levner, Eugene %T Improving the solution complexity of the scheduling problem with deadlines: A general technique %J RAIRO - Operations Research - Recherche Opérationnelle %D 2016 %P 681-687 %V 50 %N 4-5 %I EDP-Sciences %U http://geodesic.mathdoc.fr/articles/10.1051/ro/2016021/ %R 10.1051/ro/2016021 %G en %F RO_2016__50_4-5_681_0
Elalouf, Amir; Levner, Eugene. Improving the solution complexity of the scheduling problem with deadlines: A general technique. RAIRO - Operations Research - Recherche Opérationnelle, Special issue - Advanced Optimization Approaches and Modern OR-Applications, Tome 50 (2016) no. 4-5, pp. 681-687. doi: 10.1051/ro/2016021
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