Uniform-machines scheduling: Difference between revisions

Revision as of 17:42, 30 January 2024

Latest revision as of 15:49, 27 August 2025

(4 intermediate revisions by 4 users not shown)

Line 1:

{{Short description|Optimization prpblem}}

'''Uniform machine scheduling''' (also called '''uniformly-related machine scheduling''' or '''related machine scheduling''') is an [[optimization problem]] in [[computer science]] and [[Operations Research|operations research]]. It is a variant of [[optimal job scheduling]]. We are given ''n'' jobs ''J''₁, ''J''₂, ..., ''J_n'' of varying processing times, which need to be scheduled on ''m'' different machines. The goal is to minimize the [[makespan]] - the total time required to execute the schedule. The time that machine ''i'' needs in order to process job j is denoted by ''p_i,j''. In the general case, the times ''p_i,j'' are unrelated, and any matrix of positive processing times is possible. In the specific variant called ''uniform machine scheduling'', some machines are ''uniformly'' faster than others. This means that, for each machine ''i'', there is a speed factor ''s_i'', and the run-time of job ''j'' on machine ''i'' is ''p_i,j'' = ''p_j'' / ''s_i''.

In the standard [[Optimal job scheduling|three-field notation for optimal job scheduling problems]], the uniform-machine variant is denoted by '''Q''' in the first field. For example, the problem denoted by " '''Q||'''<math>C_\max</math>" is a uniform machine scheduling problem with no constraints, where the goal is to minimize the maximum completion time. A special case of uniform machine scheduling is [[identical-machinemachines scheduling]], in which all machines have the same speed. This variant is denoted by '''P''' in the first field.

In some variants of the problem, instead of minimizing the ''maximum'' completion time, it is desired to minimize the ''average'' completion time (averaged over all ''n'' jobs); it is denoted by '''Q||'''<math>\sum C_i</math>. More generally, when some jobs are more important than others, it may be desired to minimize a ''[[Weighted arithmetic mean|weighted average]]'' of the completion time, where each job has a different weight. This is denoted by '''Q||'''<math>\sum w_i C_i</math>.

Line 34 ⟶ 35:

* [[Polynomial-time approximation scheme]]s, which for any ''ε''>0, attain at most (1+ε)OPT. For minimizing the ''maximum'' completion time on two ''uniform'' machines, their algorithm runs in time <math>O(10^{2l} n)</math>, where <math>l</math> is the smallest integer for which <math>\epsilon \geq 2\cdot 10^{-l}</math>. Therefore, the run-time is in <math>O( n / \epsilon^2)</math>, so it is an [[FPTAS]]. For minimizing the ''maximum'' completion time on two ''unrelated'' machines, the run-time is <math>O(10^{l} n^2)</math> = <math>O( n^2 / \epsilon)</math>. They claim that their algorithms can be easily extended for any number of uniform machines, but do not analyze the run-time in this case.

'''Hochbaum and Shmoys'''<ref name=":02">{{Cite journal|last1=Hochbaum|first1=Dorit S.|last2=Shmoys|first2=David B.|date=1987-01-01|title=Using dual approximation algorithms for scheduling problems theoretical and practical results|journal=Journal of the ACM|volume=34|issue=1|pages=144–162|doi=10.1145/7531.7535|issn=0004-5411|s2cid=9739129|doi-access=free}}</ref> presented several approximation algorithms for any number of [[Identical-machines scheduling|''identical'' machines]]. Later,<ref>{{Cite journal|last1=Hochbaum|first1=Dorit S.|last2=Shmoys|first2=David B.|date=1988-06-01|title=A Polynomial Approximation Scheme for Scheduling on Uniform Processors: Using the Dual Approximation Approach|url=https://epubs.siam.org/doi/abs/10.1137/0217033|journal=SIAM Journal on Computing|volume=17|issue=3|pages=539–551|doi=10.1137/0217033|issn=0097-5397|url-access=subscription}}</ref> they developed a PTAS for ''uniform'' machines.

'''Epstein and Sgall'''<ref>{{Cite journal|last1=Epstein|first1=Leah|last2=Sgall|first2=Jiri|date=2004-05-01|title=Approximation Schemes for Schedulingon Uniformly Related and Identical Parallel Machines|url=https://doi.org/10.1007/s00453-003-1077-7|journal=Algorithmica|language=en|volume=39|issue=1|pages=43–57|doi=10.1007/s00453-003-1077-7|s2cid=12965369 |issn=1432-0541|url-access=subscription}}</ref> generalized the PTAS for uniform machines to handle more general objective functions. Let ''C_i'' (for ''i'' between 1 and ''m'') be the makespan of machine ''i'' in a given schedule. Instead of minimizing the objective function max(''C_i''), one can minimize the objective function max(''f''(''C_i'')), where ''f'' is any fixed function. Similarly, one can minimize the objective function sum(''f''(''C_i'')).

=== Monotonicity and Truthfulness ===

In some settings, the machine speed is the machine's private information, and we want to incentivize machines to reveal their true speed, that is, we want a [[truthful mechanism]]. An important consideration for attaining truthfulness is ''monotonicity''.<ref>{{Cite book|last1=Archer|first1=A.|last2=Tardos|first2=E.|title=Proceedings 42nd IEEE Symposium on Foundations of Computer Science |chapter=Truthful mechanisms for one-parameter agents |date=2001-10-01|chapter-url=https://ieeexplore.ieee.org/document/959924|pages=482–491|doi=10.1109/SFCS.2001.959924|isbn=0-7695-1390-5 |s2cid=11377808 }}</ref> It means that, if a machine reports a higher speed, and all other inputs remain the same, then the total processing time allocated to the machine weakly increases. For this problem:

* '''Auletta, De Prisco, Penna and Persiano'''<ref>{{Cite book|last1=Auletta|first1=Vincenzo|last2=De Prisco|first2=Roberto|last3=Penna|first3=Paolo|last4=Persiano|first4=Giuseppe|title=Stacs 2004 |chapter=Deterministic Truthful Approximation Mechanisms for Scheduling Related Machines |date=2004|editor-last=Diekert|editor-first=Volker|editor2-last=Habib|editor2-first=Michel|chapter-url=https://link.springer.com/chapter/10.1007/978-3-540-24749-4_53|series=Lecture Notes in Computer Science|volume=2996 |language=en|___location=Berlin, Heidelberg|publisher=Springer|pages=608–619|doi=10.1007/978-3-540-24749-4_53|isbn=978-3-540-24749-4}}</ref> presented a 4-approximation monotone algorithm, which runs in polytime when the number of machines is fixed.

Line 62 ⟶ 63:

[[Category:Optimal scheduling]]

[[Category:NP-complete problems]]