On computational methods for dynamic and static optimization
Pages 181 - 185
Abstract
In the 1960s the joint impact of fast digital computers and the space age stimulated the ingenuity of a number of researchers in optimization and prompted them to invent new and/or better (faster, more elegant) methods for solving, numerically, optimization problems of different types. Two areas that received much attention were trajectory optimization and parameter optimization. That is, the computational problems of determining optimal trajectories (generally, functions of time) and optimal parameter values by minimizing (maximizing) appropriate performance criteria.
References
[1]
H J Kelley Methods of gradients In Optimation Techniques G Leitmann ed Academic Press New York 1962
[2]
H J Kelley R E Kopp H G Moyer A trajectory optimization technique based upon the theory of the second variation In Progress in Astronautics and Aeronautics Vol 14 New York Academic Press 1964 pp 559--582
[3]
S R McReynolds A E Bryson Jr A successive sweep method for solving optimal programming problems Proc 1965 Joint Automatic Control Conference No 6 p 551
[4]
H J Kelley B R Uzzell S S McKay Rocket trajectory optimization by a second-order numerical technique AIAA NASA-MSC Astrodynamics Conference Houston Texas December 12--14 1967
[5]
C W Merriam III Optimization theory and the design of feedback controls McGraw-Hill New York 1964
[6]
D Q Mayne A second-order gradient method of optimizing non-linear discrete time systems Int J Control 3 1966 pp 85--95
[7]
D H Jacobson D Q Mayne Differential dynamic programming American Elsevier New York 1970
[8]
D Q Mayne Differential dynamic programming---A unified approach to the optimization of dynamic systems To appear in Advances in Control Systems C T Leondes ed 1972
[9]
R Fletcher C M Reeves Function minimization by conjugate gradients Computer Journal 7 July 1964 pp 149--154
[10]
R Fletcher M J D Powell A rapidly convergent descent method for minimization Computer Journal 6 1963 pp 163--168
[11]
M J D Powell On the convergence of a variable metric algorithm J Inst Math Applic 7 1971 p 21
[12]
D H Jacobson W Oksman An algorithm that minimizes homogeneous functions of n variables in (n + 2) iterations and rapidly minimizes general functions J Math Anal Appl 1971 To appear
[13]
E Polak Computational methods in optimization---A unified approach Academic Press New York 1971
[14]
E Polak D H Jacobson Informal Talks Spring 1971
[15]
W F Denham Review of Reference 7 IEEE Trans Automatic Control Volume 16 August 1971 pp 389--390
[16]
D H Jacobson M M Lele J L Speyer New necessary conditions of optimality for control problems with state variable inequality constraints J Math Anal Appl 35 1971 pp 255--284
[17]
B A Murtagh R W H Sargent Computational experience with quadratically convergent minimization methods Computer J Volume 13 May 1970 pp 185--194
- On computational methods for dynamic and static optimization
Recommendations
Chaotic dynamic weight particle swarm optimization for numerical function optimization
Particle swarm optimization (PSO), which is inspired by social behaviors of individuals in bird swarms, is a nature-inspired and global optimization algorithm. The PSO method is easy to implement and has shown good performance for many real-world ...
Dynamic cluster in particle swarm optimization algorithm
Particle swarm optimization is an optimization method based on a simulated social behavior displayed by artificial particles in a swarm, inspired from bird flocks and fish schools. An underlying component that influences the exchange of information ...
Sizing and layout design of truss structures under dynamic and static constraints with an integrated particle swarm optimization algorithm
Display Omitted An integrated particle swarm optimization algorithm for weight minimization of truss structures with sizing and layout variables is developed;.Optimization problems with frequency constraints and static constraints are solved;.The new ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
May 1972
1234 pages
ISBN:9781450379090
DOI:10.1145/1478873
Copyright © 1971 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Sponsors
- AFIPS: American Federation of Information Processing Societies
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 16 November 1971
Check for updates
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 118Total Downloads
- Downloads (Last 12 months)19
- Downloads (Last 6 weeks)4
Reflects downloads up to 20 Nov 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in