Postoptimal Analyses, Parametric Programming, and Related by Tomas Gal, Thomas Gal

By Tomas Gal, Thomas Gal

Foreword
For a few massive time, linear programming has been one of many equipment of operations examine which has been well known and masses utilized in Germany too, either within the literature ofthe topic and in perform. Its functions diversity from creation making plans via finance making plans and from optimization of site visitors networks via city making plans. The literature of linear programming comprises textbooks of a strictly mathematical nature as weil as programmed textbooks for people with no earlier wisdom of arithmetic. An objection often heard to extra vast dissemination of the theories of linear programming within the sensible box has been that information wh ich come in perform are instantly too inexact and too unreliable to supply the foundation for the appliance of "exact" systems like linear programming. This challenge is the place to begin of the current quantity. The inexactitude and unreliability of present info frequently can't be disputed. utilizing traditional making plans equipment, the decision of the consequences of those inaccuracies is usually very tough, if now not very unlikely. often, this can be, notwithstanding, attainable utilizing sensitivity research within the widest experience (i.e., together with postoptimal research and parametric programming), and the quantity of attempt concerned is cheap. My colleague, Professor Gal has been keen on examine during this box for a few years. His choice to adopt the writing of an advent to and interpretation of the realm of linear programming which permits us to make statements at the attainable results of knowledge adjustments, info inaccuracies, and
decision alterations on operational and different difficulties is, consequently, to be welcomed.
Sensitivity research, as interpreted within the current quantity, has been noticeable through specialists - accurately, in my view - because the bridge among natural dissemination of knowledge and selection making. there's, therefore, considerable justification for together with a quantity on such a huge topic within the "Operations Research" sequence. because the current quantity is probably going to curiosity either hose operating in linear programming and learn mathematicians, the chapters were written essentially with useful program in brain, and an abridged mathematical model has been appended to every of them. it's was hoping that it will raise the usefulness of the quantity for quite a lot of readers.
Professor Dr H.-J. Zimmermann
Aachen, July 1973

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Extra info for Postoptimal Analyses, Parametric Programming, and Related Topics

Sample text

Xm)T ofreal numbers XI, ... , Xm. The vector x is also called an m-vector, and the numbers XI, . . , Xm are also known as the elements or the coordinates of the vector x. ,A, B. , AT, BT. , Xj, Sj. At this point, several special vectors and matrices will be noted which frequently occur in the text later on. Thus, o o ek = (0, ... , 1,0, ... ,O)T = o I o o 0= (0, 0, ... O)T, 0 E IR n a null vector; The reader is referred to the (selected) textbooks for a fuH discussion of LP and/or linear algebra: rI, 3, 8, 9].

Each column of these modified constraints becomes a row in the dual. It follows from this that the dual problem has four "real variables" u (, U2, U3 , U4. The vector C of the primal problem becomes the vector b of the dual and the vector b of the primal problem becomes vector C of the dual. If maximization takes place in the primal problem, then there will be a minimization in the dual problem, and conversely; the type of the inequalities will also be converse. The dual problem we obtain is, thus: minimize f = 13u( + 20U2 + 121u3 - 8U4 subject to Ul + 5U2 - 8U3 - 4U4 ~ 3, UI - 4U2 + 22u3 - U4 ~ 8, Uj ~ O,i = I, .

Hence, (1-25) also holds. The transformation of the vector e into the basis B is carried out in accordance with the following formula (for the derivation of this relation, see, for example, [3,4]): PZT = C~B-I Ä - eT. (1-26) Each component L\Zj of the vector (1-25) is determined as folIows: T" L\Zj =P Zj -Cj = cByJ -Cj,j = I, ... ,N. (1-27) The vector pzT can be expressed as folIows: pzT =(C~B-IA-cTlc~B-I), (1-28) since the cost coefficients of the slacks are equal to zero. Finally, the following notation is introduced: 32 Abridged mathematical presentation u T = e~B-I.

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