zᵀ=
zᵀ=cbᵀB-¹N
yʲ =
yʲ = [B-¹N]ʲ
reduced cost coefficiant
-(zⱼ-cⱼ)
reformulated LP using the current BFS
min f₀ - (zᵀ - cnᵀ)xn
s.t. B-¹Nxn + xb = B-¹b
Check the optimality of the BFS. zⱼ-cⱼ≤0 for all j
the current BFS is optimal
Check the optimality of the BFS. the current BFS is optimal
zⱼ-cⱼ≤0 for all j
Check the optimality of the BFS. zⱼ-cⱼ>0 for some j and yʲ=B-¹aⱼ≤0
Then the LP is unbounded
Check the optimality of the BFS. LP is unbounded
zⱼ-cⱼ>0 for some j and yʲ=B-¹aⱼ≤0
Check the optimality of the BFS. zⱼ-cⱼ>0 for some j and yʲ=B-¹aⱼ has a positive component
the LP can be optimised further
Check the optimality of the BFS. LP can be optimised further
zⱼ-cⱼ>0 for some j and yʲ=B-¹aⱼ has a positive component
f₀ =
cbᵀB-¹b
the objective value for the BFS
How to check if an objective value is optimal
Simplex algorithm:
Theorem. Convergence.
In the absence of degeneracy and assuming feasibility the simplex method stops in a finite number of iteration, either with an optimal BFS or with the conclusion that the optimal value is unbounded,
degeneracy
components of the BFS are zero.
Initial Tableu:
col: xb
row: zero
0
Initial Tableu:
col: xn
row: zero
zⱼ-cⱼ
Initial Tableu:
col: RHS
row: zero
cbᵀB-¹b
Initial Tableu:
col: xn
row: xb
B-¹N
Initial Tableu:
col: RHS
row: xb
B-¹b=b*
Initial Tableu:
col: xb
row: xb
Identity
How to pivot
minimum ratio test for r
bᵣ/yᵣₖ = min {bᵢ/yᵢₖ: yᵢₖ>0}
simplex algorithm (tableu format):