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The revised multiphase simplex algorithm used in me 6103 – optimization in engineering design. The algorithm is presented step by step, including initialization, pricing vector development, selection of entering non-basic variable, updating the entering column, determination of the leaving basic variable, and pivot. The convergence check is also explained.
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ME 6103 – Optimization in Engineering Design (Bras)
Find v so as to
lexmin u T = { c (1)T v , ..., c (k)T v , ..., c (K)T v }
subject to
Av = b
v ≥ 0 where v =
x
x
d
d
Set k = 1. Initially, all variables are unchecked.
(k)T = c B
(k)T B
rj (k) = (k)T a j - cj (k) for all j N’
where N’ is the set of non-basic and unchecked variables.
(k) as computed in step 3. If none are
positive, proceed to step 8. Otherwise, select the non-basic variable with the most positive rj (k) (ties
may be broken arbitrarily) as the entering variable. Designate this variable as vq.
q = B
present representation of = B
p
j , p
min
i | i , q 0
i
i , q
Again, ties may be broken arbitrarily. The basic variable associated with row i=p is the leaving
variable, v Bp.
If none exists, the entering variable is unbounded (all i,q ≤ 0). This condition will not occur as
long as v ≥ 0 and c
(k) ≥ 0 for all k. In such case no elements of u
T can become less than 0 and
therefore are always bounded.
solution has been found.
a) if all r j
(k) as computed in step 3 are negative, or
b) if k = K (where K = the number of priority levels, or terms in u T ).
Dr. Bert Bras Telephone 404-894-9667 Fax 404-894-9342 E-mail [email protected]
ME 6103 – Optimization in Engineering Design (Bras)
Otherwise, “check” all non-basic variables associated with a negative rj (k) , set k=k+1 and return to
step 2.
Dr. Bert Bras Telephone 404-894-9667 Fax 404-894-9342 E-mail [email protected]