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 48.
x. lappuse
... compact sets in separable normed spaces 262 Strong separation of finite sets in the Hadamard space 265 References 269 13 A SEMI - INFINTE OPTIMIZATION APPROACH TO OPTI- MAL SPLINE TRAJECTORY PLANNING OF MECHANI- CAL MANIPULATORS 271 ...
... compact sets in separable normed spaces 262 Strong separation of finite sets in the Hadamard space 265 References 269 13 A SEMI - INFINTE OPTIMIZATION APPROACH TO OPTI- MAL SPLINE TRAJECTORY PLANNING OF MECHANI- CAL MANIPULATORS 271 ...
9. lappuse
... compact in Rm1 Assume that m variables are required in the linear system u1 Pi - ci > Ꭲ 0 , for all i Є I. Assume further that u1 Po - Ꭲ d≥ 0 , whenever u1 Pi – ci ≥ 0 , for all i € I. - Then there exists λ¿ ≥ 0 , i Є I , with at ...
... compact in Rm1 Assume that m variables are required in the linear system u1 Pi - ci > Ꭲ 0 , for all i Є I. Assume further that u1 Po - Ꭲ d≥ 0 , whenever u1 Pi – ci ≥ 0 , for all i € I. - Then there exists λ¿ ≥ 0 , i Є I , with at ...
13. lappuse
... compact . Then vp ( U ) = vD ( U ) , and the primal objective function value of vp ( U ) is attained . Remark 4.1 Adjoin the inequality −u2 ≥ −U to Example 4.1 and denote the program value of the new dual by v5 . Then v5 = 0 ...
... compact . Then vp ( U ) = vD ( U ) , and the primal objective function value of vp ( U ) is attained . Remark 4.1 Adjoin the inequality −u2 ≥ −U to Example 4.1 and denote the program value of the new dual by v5 . Then v5 = 0 ...
14. lappuse
... compact set of real co- efficients . Consider the fully regularized , general dual programs of Section 4.1 having variables { uo , u } and { \ ¿ , i € I , v † , v ̄ } respectively . There exist non - Archimedean dual optimal solutions ...
... compact set of real co- efficients . Consider the fully regularized , general dual programs of Section 4.1 having variables { uo , u } and { \ ¿ , i € I , v † , v ̄ } respectively . There exist non - Archimedean dual optimal solutions ...
51. lappuse
Esat sasniedzis šīs grāmatas aplūkošanas reižu limitu.
Esat sasniedzis šīs grāmatas aplūkošanas reižu limitu.
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