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Jack Edmonds

Jack Edmonds is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Jack Edmonds rather than just read about it. In short: Jack R. Edmonds (born April 5, 1934) is an American-born and educated computer scientist and mathematician who lived and worked in Canada for much of his life.

Jack Edmonds — main illustration
Jack Edmonds — illustration

Key takeaways

  • Jack Edmonds belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Jack Edmonds to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Jack Edmonds from memory before moving on to harder problems.

Reference excerpt

Jack R. Edmonds (born April 5, 1934) is an American-born and educated computer scientist and mathematician who lived and worked in Canada for much of his life. He has made fundamental contributions to the fields of combinatorial optimization, polyhedral combinatorics, discrete mathematics and the theory of computing. He was the recipient of the 1985 John von Neumann Theory Prize.

Early career Edmonds attended McKinley Technology High School, graduating in 1952; and has talked about the influence this school had on his career (for instance at his 2014 NIST Gallery induction ). Edmonds attended Duke University before completing his undergraduate degree at George Washington University in 1957. He thereafter received a master's degree in 1960 at the University of Maryland under Bruce L. Reinhart with a thesis on the problem of embedding graphs into surfaces. From 1959 to 1969 he worked at the National Institute of Standards and Technology (then the National Bureau of Standards), and was a founding member of Alan Goldman’s newly created Operations Research Section in 1961. Goldman proved to be a crucial influence by enabling Edmonds to work in a RAND Corporation-sponsored workshop in Santa Monica, California. It is here that Edmonds first presented his findings on defining a class of algorithms that could run more efficiently. Most combinatorics scholars, during this time, were not focused on algorithms. However Edmonds was drawn to them and these initial investigations were key developments for his later work between matroids and optimization. He spent the years from 1961 to 1965 on the subject of NP versus P and in 1966 originated the conjectures NP ≠ P and NP ∩ coNP = P.

Research Edmonds's 1965 paper “Paths, Trees and Flowers” was a preeminent paper in initially suggesting the possibility of establishing a mathematical theory of efficient combinatorial algorithms. One of his earliest and notable contributions is the blossom algorithm for constructing maximum matchings on graphs, discovered in 1961 and published in 1965. This was the first polynomial-time algorithm for maximum matching in graphs. Its generalization to weighted graphs was a conceptual breakthrough in the use of linear programming ideas in combinatorial optimization. It sealed in the importance of there being proofs, or "witnesses", that the answer for an instance is yes and there being proofs, or "witnesses", that the answer for an instance is no. In this blossom algorithm paper, Edmonds also characterizes feasible problems as those solvable in polynomial time; this is one of the origins of the Cobham–Edmonds thesis. A breakthrough of the Cobham–Edmonds thesis, was defining the concept of polynomial time characterising the difference between a practical and an impractical algorithm (in modern terms, a tractable problem or intractable problem). Today, problems solvable in polynomial time are called the complexity class PTIME, or simply P. Edmonds's paper “Maximum Matching and a Polyhedron with 0-1 Vertices” along with his previous work gave astonishing polynomial-time algorithms for the construction of maximum matchings. Most notably, these papers demonstrated how a good characterization of the polyhedron associated with a combinatorial optimization problem could lead, via the duality theory of linear programming, to the construction of an efficient algorithm for the solution of that problem. Additional landmark work of Edmonds is in the area of matroids. He found a polyhedral description for all spanning trees of a graph, and more generally for all independent sets of a matroid. Building on this, as a novel application of linear programming to discrete mathematics, he proved the matroid intersection theorem, a very general combinatorial min-max theorem which, in modern terms, showed that the matroid intersection problem lay in both NP and co-NP. Edmonds is well known for his theorems on max-weight branching algorithms and packing edge-disjoint branchings and his work with Richard Karp on faster flow algorithms. The Edmonds–Gallai decomposition theorem describes finite graphs from the point of view of matchings. He introduced polymatroids, submodular flows with Richard Giles, and the terms clutter and blocker in the study of hypergraphs. A recurring theme in his work is to seek algorithms whose time complexity is polynomially bounded by their input size and bit-complexity.

Career From 1969 on, with the exception of 1991–1993, he held a faculty position at the Department of Combinatorics and Optimization at the University of Waterloo's Faculty of Mathematics where his research encompassed combinatorial optimization problems and associated polyhedra. He supervised the doctoral work of a dozen students in this time. He gave courses or spent research leaves at Duke University, George Washington University, the University of Maryland, Stanford, Princeton, Cornell, as well as universities in China, Leuven (Belgium), Copenhagen, Southern Denmark (Odense), Paris, Marseille, Grenoble (France), as well as Bonn and Cologne (Germany). From 1991 to 1993, he was involved in a dispute ("the Edmonds affair") with the University of Waterloo, wherein the university claimed that a letter submitted constituted a letter of resignation, which Edmonds denied. The conflict was resolved in 1993, and he returned to the university. Edmonds retired from the University of Waterloo in 1999.

Awards and honors Edmonds was the 1985 recipient of the John von Neumann Theory Prize. In 2001 his paper, "Paths, Trees and Flowers" was honoured as an Outstanding Publication by the National Institute of Standards and Technology in their celebratory edition of A Century of Excellence in Measurements Standards and Technology He was elected to the 2002 class of Fellows of the Institute for Operations Research and the Management Sciences. In 2006 the Queen of Denmark presented Edmonds with an Honorary Doctorate from the University of Southern Denmark. In 2014 he was honored as a Distinguished Scientist and inducted into the National Institute of Standards and Technology's Gallery. The fifth Aussois Workshop on Combinatorial Optimization in 2001 was dedicated to him.

Personal life Jack's son Jeff Edmonds is a professor of computer science at York University, and his wife Kathie Cameron is a professor of mathematics at Laurier University.

See also Edmonds matrix List of University of Waterloo people

References

… excerpt ends here. Continue reading the full article.

Illustrations

Jack Edmonds illustration

Worked examples

Example 1 — a first encounter with Jack Edmonds

Start with the simplest possible case. Write down what Jack Edmonds claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Jack Edmonds before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Jack Edmonds ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Jack Edmonds

In research
Jack Edmonds appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Jack Edmonds in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Jack Edmonds is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1934 births, 20th-century Canadian mathematicians, Academic staff of the University of Waterloo, so understanding it makes those chapters shorter.
In everyday life
Look for Jack Edmonds outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Jack Edmonds in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Jack Edmonds means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Jack Edmonds out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Jack Edmonds in simple terms?

Jack R. Edmonds (born April 5, 1934) is an American-born and educated computer scientist and mathematician who lived and worked in Canada for much of his life.

Why does Jack Edmonds matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Jack Edmonds?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Jack Edmonds.

Tags

  • 1934 births
  • 20th-century Canadian mathematicians
  • Academic staff of the University of Waterloo
  • Canadian computer scientists
  • Combinatorial optimization
  • Combinatorialists
  • Fellows of the Institute for Operations Research and the Management Sciences
  • John von Neumann Theory Prize winners
  • Living people
  • National Institute of Standards and Technology people

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