Journal article
HEURISTIC NONSERIAL DYNAMIC PROGRAMMING FOR LARGE PROBLEMS
Engineering optimization, v 4(4), pp 167-178
01 Jan 1980
Abstract
Dynamic programming is an extremely powerful optimization approach used for the solution of problems which can be formulated to exhibit a serial stage-state structure. However, many design problems are not serial but have highly connected interdependent structures. Existing methods, for the solution of nonserial problems require the problem to possess a certain structure or limit the size of the problem due to storage and computational time requirements. The aim of this paper is to show that nonserial problems can be solved by the use of dynamic programming incorporating algorithms based on heuristics. Two such algorithms are developed using artificial intelligence concepts of estimating the likelihood of future results on present decisions. The algorithms are explained in detail, A small problem is solved and the results of testing them on large scale problems are given. The method is then used to solve a problem drawn from the literature.
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Details
- Title
- HEURISTIC NONSERIAL DYNAMIC PROGRAMMING FOR LARGE PROBLEMS
- Creators
- MICHAEL A. Rosenman - The University of SydneyJOHN S. Gero - The University of Sydney
- Publication Details
- Engineering optimization, v 4(4), pp 167-178
- Publisher
- Taylor & Francis Group; READING
- Number of pages
- 12
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology)
- Web of Science ID
- WOS:A1980KL36300001
- Scopus ID
- 2-s2.0-0019298981
- Other Identifier
- 991022203049704721