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 87.
7. lappuse
... obtain the following dual programming pair , where for convenience we retain the same number of variables in the linear inequality system as in ( 1.1 ) . The notation r = 1 , m is typical Russian denoting , r = 1 , ... m . Program GLP ...
... obtain the following dual programming pair , where for convenience we retain the same number of variables in the linear inequality system as in ( 1.1 ) . The notation r = 1 , m is typical Russian denoting , r = 1 , ... m . Program GLP ...
8. lappuse
... obtain , \ Um + 1 ( x ) ≥ \ Σ Um + 1 ( xi ) \ i / λ = Σ Um + 1 ( Xi ) \ i . Since the feasible points were arbitrary for their respective programs , it follows that Z > M. Hence , Z = M. □ Under the convexity / concavity assumption on ...
... obtain , \ Um + 1 ( x ) ≥ \ Σ Um + 1 ( xi ) \ i / λ = Σ Um + 1 ( Xi ) \ i . Since the feasible points were arbitrary for their respective programs , it follows that Z > M. Hence , Z = M. □ Under the convexity / concavity assumption on ...
9. lappuse
... obtain paper by Tschernikow is [ 86 ] . ) Tschernikow was the thesis advisor of Nikolay Astaf'ev of the Institute of ... obtaining a canonically closed representation equivalent to ON THE 1962-1972 DECADE OF SIP : A SUBJECTIVE VIEW 9 ...
... obtain paper by Tschernikow is [ 86 ] . ) Tschernikow was the thesis advisor of Nikolay Astaf'ev of the Institute of ... obtaining a canonically closed representation equivalent to ON THE 1962-1972 DECADE OF SIP : A SUBJECTIVE VIEW 9 ...
10. lappuse
Recent Advances Miguel Ángel Goberna, Marco A. López. The idea of obtaining a canonically closed representation equivalent to a given semi - infinite system was of interest during this time with Zhu's 1966 index of degeneracy , [ 91 ] ...
Recent Advances Miguel Ángel Goberna, Marco A. López. The idea of obtaining a canonically closed representation equivalent to a given semi - infinite system was of interest during this time with Zhu's 1966 index of degeneracy , [ 91 ] ...
11. lappuse
... obtained by using any ordered field . An opposite sign property algorithm for purification to an extreme point solution was developed in 1963 , first for ordinary linear pro- gramming and , almost simultaneously , for linear semi ...
... obtained by using any ordered field . An opposite sign property algorithm for purification to an extreme point solution was developed in 1963 , first for ordinary linear pro- gramming and , almost simultaneously , for linear semi ...
Saturs
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