Complex systems and the solution of extremal problems

Mikhalevich, V. S.; Ermol’ev, Yu. M.; Shkurba, V. V.; Shor, N. Z.

doi:10.1007/bf01071594

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…Methods of sequential analysis of variants which are conceptually close to the method of dynamic programming were developed by Mikhalevich and his collaborators [186][187][188][189].…”

Section: Ovmentioning

confidence: 99%

“…The following surveys and lectures are devoted to the methods of approximate and numerical solution of problemsin optimal control: Budak and Vasil'ev [57], Gabasov and Kirillov [74], Isaevand Sonin [376], Kolmanovskii and Chernous'ko [127], Krasovskii [139], Krasovskii, Gavrilov, Letov, and Pugachev [141], Krasovskii and Moiseev [144], Letov [168], Litovchenko [175], Mikhalevich, Ermol'ev, Shkurb, andShor [188], Moiseev [192][193], Moiseev and Lebedev [441], Polyak [226], Chernous'ko [274], Bell [302], Fleming [348], Kelley [393], Kopp [403], Larson [410], [411], Mangasarian [428], Miele [439], Paiewonski [449], Polak [452], Tabak [477], Tapley and Lewallen [480], and others.…”

Section: Ovmentioning

confidence: 99%

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Computational and approximate methods of optimal control

Chernousko¹,

Kolmanovskii²

1979

J Sov Math

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“…Methods of sequential analysis of variants which are conceptually close to the method of dynamic programming were developed by Mikhalevich and his collaborators [186][187][188][189].…”

Section: Ovmentioning

confidence: 99%

Section: Ovmentioning

confidence: 99%

Computational and approximate methods of optimal control

Chernousko¹,

Kolmanovskii²

1979

J Sov Math

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“…In case h ≡ 0, this decomposition method was considered in [14]. However, even solution of all the partial problems of form (5) may appear too expensive.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Partial Linearization Method for Optimization Problems on Product Sets

Konnov

2017

J Optim Theory Appl

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We suggest an adaptive version of a partial linearization method for composite optimization problems. The goal function is the sum of a smooth function and a non necessary smooth convex separable function, whereas the feasible set is the corresponding Cartesian product. The method consists in selective componentwise steps together with a special control of a tolerance sequence. This technique is destined to reduce the computational expenses per iteration and maintain the basic convergence properties. We also establish its convergence rates and describe some examples of applications. Preliminary results of computations illustrate usefulness of the new method.

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Certain integral properties of information systems of hierarchic type

Kozachkov¹

1975

Cybern Syst Anal

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Complex systems and the solution of extremal problems

Cited by 5 publications

References 13 publications

Computational and approximate methods of optimal control

Computational and approximate methods of optimal control

An Adaptive Partial Linearization Method for Optimization Problems on Product Sets

Certain integral properties of information systems of hierarchic type

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