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E. J. Beltrami

dblp:74/707 · also Edward J. Beltrami · DBLP profile ↗
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3ranked-venue papers
3as first author
0since 2021 · last 1974
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 first-authorComputer networks · 1 · 1 first-authorTheory of computation · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Mathematical optimization · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Mathematical optimization
black-box optimization		 0.011972
An Adaptive Random Search Algorithm for Constrained Minimization · IEEE Trans. Computers 1972
Mathematical optimization
constrained optimization		 0.011972
An Adaptive Random Search Algorithm for Constrained Minimization · IEEE Trans. Computers 1972
Mathematical optimization
continuous optimization		 0.011972
An Adaptive Random Search Algorithm for Constrained Minimization · IEEE Trans. Computers 1972
Mathematical optimization › heuristic optimization
stochastic search		 0.011972
An Adaptive Random Search Algorithm for Constrained Minimization · IEEE Trans. Computers 1972

Methods — techniques the papers use, named apart from their topics

penalty method · 0.0pattern search · 0.0
YearPublicationVenuePosition
1974 Networks and vehicle routing for municipal waste collection
abstract
Abstract Vehicle routing for municipal waste collection encompasses a variety of problems. In this paper, we explore the techniques we have developed for solving some of these problems.
E. J. Beltrami, Lawrence Bodin
 Networks1
1972 An Adaptive Random Search Algorithm for Constrained Minimization
abstract
The well-known pattern search method has been randomized by Lawrence and Steiglitz [4] in order to augment its ability to adapt to direction. In this note we introduce other refinements in order to make it more adaptive in step size, and the use of penalty terms is incorporated as so to accommodate constraints. This yields an algorithm that appears to be robust and reliable, as verified by numerical experimentation. Moreover, the method has low storage requirements and is insensitive to the initial choice of a search radius.
E. J. Beltrami, Joseph Paul Indusi
 IEEE Trans. Computers1
1967 On Infinite-Dimensional Convex Programs
E. J. Beltrami
 J. Comput. Syst. Sci.1