Semi-Infinite Programming: Recent AdvancesMiguel Ángel Goberna, Marco A. López Springer Science & Business Media, 2013. gada 11. nov. - 386 lappuses Semi-infinite programming (SIP) deals with optimization problems in which either the number of decision variables or the number of constraints is finite. This book presents the state of the art in SIP in a suggestive way, bringing the powerful SIP tools close to the potential users in different scientific and technological fields. The volume is divided into four parts. Part I reviews the first decade of SIP (1962-1972). Part II analyses convex and generalised SIP, conic linear programming, and disjunctive programming. New numerical methods for linear, convex, and continuously differentiable SIP problems are proposed in Part III. Finally, Part IV provides an overview of the applications of SIP to probability, statistics, experimental design, robotics, optimization under uncertainty, production games, and separation problems. Audience: This book is an indispensable reference and source for advanced students and researchers in applied mathematics and engineering. |
No grāmatas satura
1.–5. rezultāts no 46.
3. lappuse
... primal variables occurring within an internal optimization . A second major theme was the introduction of an " infinity " into systems of semi - infinite linear inequalities , a manifestation of the " probing " between analysis and ...
... primal variables occurring within an internal optimization . A second major theme was the introduction of an " infinity " into systems of semi - infinite linear inequalities , a manifestation of the " probing " between analysis and ...
4. lappuse
... Primal Program vp = inf u TM P。, u € Rm subject to Dual Program VD = sup Σie¡ Ciλi , di E R for i Є I subject to uT P¿ > ci , for all i € I Σετ Ziel Pixi = Po , Ai > 0 , with only finitely many λi ‡ 0 . ( 1.1 ) At various places ...
... Primal Program vp = inf u TM P。, u € Rm subject to Dual Program VD = sup Σie¡ Ciλi , di E R for i Є I subject to uT P¿ > ci , for all i € I Σετ Ziel Pixi = Po , Ai > 0 , with only finitely many λi ‡ 0 . ( 1.1 ) At various places ...
5. lappuse
... primal and dual programs . Then Hence , Ꭲ ut Po≥ Σcidi . ΕΙ vp > VD . ( 1.5 ) If the inequality in ( 1.5 ) is strict , then there is a duality gap . When the values are equal , the terminology duality equality is used . Linear semi ...
... primal and dual programs . Then Hence , Ꭲ ut Po≥ Σcidi . ΕΙ vp > VD . ( 1.5 ) If the inequality in ( 1.5 ) is strict , then there is a duality gap . When the values are equal , the terminology duality equality is used . Linear semi ...
6. lappuse
... primal optimizing variables which usually occur within an internal optimization . This duality feature had also been achieved in papers by Eisen- berg [ 37 ] and Rockafellar [ 77 ] . The results appearing in [ 11 ] prompted the 1964 ...
... primal optimizing variables which usually occur within an internal optimization . This duality feature had also been achieved in papers by Eisen- berg [ 37 ] and Rockafellar [ 77 ] . The results appearing in [ 11 ] prompted the 1964 ...
8. lappuse
... primal program in ( 1.1 ) under the data structure of the given coefficient functions . Constructing the formal semi - infinite dual program to Program Dual GLP yields the classical moment problem ( see [ 65 ] , [ 52 ] , and [ 57 ] ...
... primal program in ( 1.1 ) under the data structure of the given coefficient functions . Constructing the formal semi - infinite dual program to Program Dual GLP yields the classical moment problem ( see [ 65 ] , [ 52 ] , and [ 57 ] ...
Saturs
ON STABILITY OF GUARANTEED ESTIMATION | 14 |
References | 34 |
75 | 40 |
2 | 45 |
ASYMPTOTIC CONSTRAINT QUALIFICATIONS | 75 |
VEX SEMIINFINITE PROGRAMMING | 101 |
6 | 120 |
Alexander Shapiro | 135 |
8 | 217 |
ANALYTIC | 221 |
ON SOME APPLICATIONS OF LSIP TO PROBABILITY | 235 |
References | 254 |
References | 269 |
15 | 325 |
Numerical Results | 345 |
207 | 348 |
Citi izdevumi - Skatīt visu
Semi-Infinite Programming: Recent Advances Miguel Ángel Goberna,Marco A. López Ierobežota priekšskatīšana - 2001 |
Semi-Infinite Programming: Recent Advances Miguel ngel Goberna,Marco A. L pez Priekšskatījums nav pieejams - 2001 |
Bieži izmantoti vārdi un frāzes
algorithm Applications Assume assumption asymptotic Banach space Charnes compact sets computation cone consider constraint qualification convergence Convex Analysis convex functions convex inequality convex programming convex set cutting plane defined denote dual problem duality theory equivalent example exists feasible set feasible solution finite number ft(x fuzzy numbers fuzzy sets given global error bound Hence holds hyperplane implies infinite interval iteration K. O. Kortanek Lemma linear programming linear semi-infinite programming lower semicontinuous LSIP Mathematical Programming method minimizer moment problem nonempty norm obtain Operations Research optimal solution optimization problem parameter previsions primal problem of moments Proof Proposition result satisfied Section semi-infinite optimization semi-infinite programming problems sequence solution set solving Step sup-function t₁ Theorem 3.1 topology val(CLP val(D val(P vector weak PLV property αΕΩ ΘΕΩ