Computational Progress in Linear and Mixed Integer Programming
Gurobi_Progress_LP_MIP
Gurobi_Progress_LP_MIP
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Example 3: A typical situation<br />
today – Supply-cha<strong>in</strong> schedul<strong>in</strong>g<br />
▸<br />
▸<br />
▸<br />
Model description:<br />
◦ Weekly model, daily buckets: Objective to m<strong>in</strong>imize<br />
end-of-day <strong>in</strong>ventory.<br />
◦ Production (s<strong>in</strong>gle facility), <strong>in</strong>ventory, shipp<strong>in</strong>g<br />
(trucks), wholesalers (dem<strong>and</strong> known)<br />
Initial model<strong>in</strong>g phase<br />
◦ Simplified prototype + complicat<strong>in</strong>g constra<strong>in</strong>ts<br />
(production run group<strong>in</strong>g req’t, m<strong>in</strong> truck<br />
constra<strong>in</strong>ts)<br />
◦ RESULT: Couldn’t get good feasible solutions.<br />
Decomposition approach<br />
◦ Talk to current schedul<strong>in</strong>g team: They first decide<br />
on “producibles” schedule. Simulate us<strong>in</strong>g heuristics.<br />
◦ Fixed model: Fix variables <strong>and</strong> run MIP<br />
© 2015 Gurobi Optimization<br />
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