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==Dynamic programming==
At the beginning of the 1970s, it was observed that a large class of combinatorial optimization problems defined on graphs could be efficiently solved by non serial [[dynamic programming]] as long as the graph had a bounded ''dimension'',
As an example, consider the problem of finding the [[maximum independent set]] in a graph of treewidth ''k''. To solve this problem, first choose one of the nodes of the tree decomposition to be the root, arbitrarily. For a node ''X<sub>i</sub>'' of the tree decomposition, let ''D<sub>i</sub>'' be the union of the sets ''X<sub>j</sub>'' descending from ''X<sub>i</sub>''. For an independent set ''S'' ⊂ ''X<sub>i</sub>'', let ''A''(''S'',''i'') denote the size of the largest independent subset ''I'' of ''D<sub>i</sub>'' such that ''I'' ∩ ''X<sub>i</sub>'' = ''S''. Similarly, for an adjacent pair of nodes ''X<sub>i</sub>'' and ''X<sub>j</sub>'', with ''X<sub>i</sub>'' farther from the root of the tree than ''X<sub>j</sub>'', and an independent set ''S'' ⊂ ''X<sub>i</sub>'' ∩ ''X<sub>j</sub>'', let ''B''(''S'',''i'',''j'') denote the size of the largest independent subset ''I'' of ''D<sub>i</sub>'' such that ''I'' ∩ ''X<sub>i</sub>'' ∩ ''X<sub>j</sub>'' = ''S''. We may calculate these ''A'' and ''B'' values by a bottom-up traversal of the tree:
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| journal = Journal of Algorithms
| volume = 8 | issue = 2 | year = 1987 | pages = 216–235 | doi = 10.1016/0196-6774(87)90039-3}}.
*{{citation
| last1 = Bertelé | first1 = Umberto
| last2 = Brioschi | first2 = Francesco
| title = Nonserial Dynamic Programming
| year = 1972
| publisher = Academic Press
| isbn = 0-12-093450-7}}.
*{{citation
| last = Bodlaender | first = Hans L. | authorlink = Hans L. Bodlaender
|