Källén–Lehmann spectral representation: Difference between revisions

Revision as of 09:14, 23 August 2013

Lawler’s algorithm is a powerful technique for solving a variety of constrained scheduling problems.^[1] The algorithm handles any precedence constraints. It schedules a set of simultaneously arriving tasks on one processor with precedence constraints to minimize maximum tardiness or lateness. Precedence constraints occur when certain jobs must be completed before other jobs can be started.

Objective Functions

The objective function is assumed to be in the form $min\,max_{0\leq i\leq n}\,g_{i}(F_{i})$ , where $g_{i}$ is any nondecreasing function and $F_{i}$ is the flow time.^[2] When $g_{i}(F_{i})=F_{i}-d_{i}=L_{i}$ , the objective function corresponds to minimizing the maximum lateness, where $d_{i}$ is due time for job $i$ and $L_{i}$ lateness of job $i$ . Another expression is $g_{i}(F_{i})=max{(F_{i}-d_{i},0)}$ , which corresponds to minimizing the maximum tardiness.

References

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Additional readings

Michael Pinedo. Scheduling: theory, algorithms, and systems. 2008. ISBN 978-0-387-78934-7
Conway, Maxwell, Miller. Theory of Scheduling. 1967. ISBN 0-486-42817-6

↑ Steven Nahmias. Production and Operations Analysis. 2008. ISBN 978-0-07-126370-2
↑ Joseph Y-T. Leung. Handbook of scheduling: algorithms, models, and performance analysis. 2004. ISBN 978-1-58488-397-5

[1] Steven Nahmias. Production and Operations Analysis. 2008. ISBN 978-0-07-126370-2

[2] Joseph Y-T. Leung. Handbook of scheduling: algorithms, models, and performance analysis. 2004. ISBN 978-1-58488-397-5

[1]

[2]

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+'''Lawler’s algorithm''' is a powerful technique for solving a variety of constrained scheduling problems.<ref>Steven Nahmias. Production and Operations Analysis. 2008. ISBN 978-0-07-126370-2</ref> The [[algorithm]] handles any precedence constraints. It schedules a set of simultaneously arriving tasks on one processor with precedence constraints to minimize maximum tardiness or lateness. Precedence constraints occur when certain jobs must be completed before other jobs can be started.
+==Objective Functions==
+The [[objective function]] is assumed to be in the form <math>min \, max_{0\le i \le n} \, g_i(F_i)</math>, where <math>g_i</math> is any [[nondecreasing function]] and <math>F_i</math> is the flow time.<ref>Joseph Y-T. Leung. Handbook of scheduling: algorithms, models, and performance analysis. 2004. ISBN 978-1-58488-397-5</ref> When <math>g_i (F_i) = F_i - d_i = L_i</math>, the objective function corresponds to minimizing the maximum lateness, where <math>d_i</math> is due time for job <math>i</math> and <math>L_i</math> lateness of job <math>i</math>. Another expression is <math>g_i (F_i) = max {(F_i-d_i,0)}</math>, which corresponds to minimizing the maximum tardiness.
+==References==
+{{Reflist}}
+==Additional readings==
+*Michael Pinedo. Scheduling: theory, algorithms, and systems. 2008. ISBN 978-0-387-78934-7
+*Conway, Maxwell, Miller. Theory of Scheduling. 1967. ISBN 0-486-42817-6
+[[Category:Production and manufacturing]]
+[[Category:Operations research]]
+[[Category:Industrial engineering]]

Källén–Lehmann spectral representation: Difference between revisions

Revision as of 09:14, 23 August 2013

Objective Functions

References

Additional readings

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