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Illustrative Example of Branch-and-Bound
John Mitchell
The most infeasible integer variable is used
as the branching variable, and best-bound is used for node selection.
Each box in the tree contains the optimal solution to the relaxation
and its value.
Notation:
- L is the set of active nodes.
-
is the value of the best known integer solution.
This is initialized to
.
- ziR is the value of the relaxation of problem
.
Progress of the algorithm:
- 1.
- Initially, L consists of just the problem
.
The solution to the LP relaxation is x10=2.5, x20=3.75,
with value z0R=59.5.
The most infeasible integer variable is x1,
so two new subproblems are created,
where
and
where
,
and
.
- 2.
- Both problems in L have the same bound 59.5,
so assume the algorithm arbitrarily selects
.
The optimal solution to the LP relaxation of
is x11=3, x21=2.5, with value z1R=59.
The most infeasible integer variable is x2,
so two new subproblems of
are created,
where
and
where
,
and now
.
- 3.
- The algorithm next examines
,
since this is
the problem with the best bound.
The optimal solution to the LP-relaxation is
x12=2, x22=4, with value z2R=58.
Since x2 is integral feasible,
can be updated to 58
and
is fathomed.
- 4.
- Both of the two problems remaining in L
have best bound greater than 58, so neither can yet be fathomed.
Since these two subproblems have the same bound 59,
assume the algorithm arbitrarily selects
to examine next.
The LP relaxation to this problem is infeasible, since it requires
that x satisfy
,
and
simultaneously. Therefore,
,
and this node can be fathomed
by infeasibility.
- 5.
- That leaves the single problem
in L.
The solution to the LP relaxation of this problem is
x14=3.2, x24=2, with value z4R=57.6.
Since
,
this subproblem can also be
fathomed by bounds.
The set L is now empty, so x2 is optimal for the
integer programming problem
.
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John E Mitchell
2001-03-22