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MaxCliqueDyn algorithm

MaxCliqueDyn algorithm is a computer science 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 MaxCliqueDyn algorithm rather than just read about it. In short: The MaxCliqueDyn algorithm is an algorithm for finding a maximum clique in an undirected graph. MaxCliqueDyn is based on the MaxClique algorithm, which finds a maximum clique of bounded size.

MaxCliqueDyn algorithm — main illustration
MaxCliqueDyn algorithm — illustration

Key takeaways

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

Reference excerpt

The MaxCliqueDyn algorithm is an algorithm for finding a maximum clique in an undirected graph. MaxCliqueDyn is based on the MaxClique algorithm, which finds a maximum clique of bounded size. The bound is found using a coloring algorithm. MaxCliqueDyn extends MaxClique to include dynamically varying bounds. This algorithm was designed by Janez Konc and its description was published in 2007. In comparison to earlier algorithms, MaxCliqueDyn has an improved coloring algorithm (ColorSort) and applies tighter, more computationally expensive upper bounds on a fraction of the search space. Both improvements reduce time to find maximum clique. In addition to reducing time, the improved coloring algorithm also reduces the number of steps needed to find a maximum clique.

MaxClique algorithm The MaxClique algorithm is the basic algorithm from which MaxCliqueDyn is extended. The pseudocode of the algorithm is:

procedure MaxClique(R, C) is Q = Ø, Qmax = Ø

while R ≠ Ø do choose a vertex p with a maximum color C(p) from set R R := R\{p} if |Q| + C(p)>|Qmax| then Q := Q ⋃ {p} if R ⋂ Γ(p) ≠ Ø then obtain a vertex-coloring C' of G(R ⋂ Γ(p)) MaxClique(R ⋂ Γ(p), C') else if |Q|>|Qmax| then Qmax := Q Q := Q\{p} else return end while

where Q is a set of vertices of the currently growing clique, Qmax is a set of vertices of the largest clique currently found, R is a set of candidate vertices, Γ(p) is the set of all vertices that are adjacent to p, and C its corresponding set of color classes. The MaxClique algorithm recursively searches for a maximum clique by adding and removing vertices to and from Q.

Coloring algorithms

Approximate coloring algorithm MaxClique uses an approximate coloring algorithm to obtain set of color classes C. In the approximate coloring algorithm, vertices are colored one by one in the same order as they appear in a set of candidate vertices R, so that if the next vertex p is non-adjacent to all vertices in the same color class, it is added to this class, and if p is adjacent to at least one vertex in every one of existing color classes, it is put into a new color class. The MaxClique algorithm returns vertices R ordered by their colors. Vertices v ∈ R {\displaystyle v\in R} with colors C ( v ) < | Q m a x | − | Q | + 1 {\displaystyle C(v)<{|Q_{max}|}-{|Q|}+1} are never added to the current clique Q. Therefore, sorting those vertices by color is of no use to MaxClique algorithm.

ColorSort The ColorSort algorithm improves on the approximate coloring algorithm by taking into consideration the above observation. Each vertex is assigned to a color class C k {\displaystyle C_{k}} . If k < | Q m a x | − | Q | + 1 {\displaystyle k<{|Q_{max}|}-{|Q|}+1} , the vertex is moved to the set R (behind the last vertex in R). If k ≥ | Q m a x | − | Q | + 1 {\displaystyle k\geq {|Q_{max}|}-{|Q|}+1} , then the vertex stays in C k {\displaystyle C_{k}} and is not moved to R. At the end, all of the vertices remaining in C k {\displaystyle C_{k}} (where k ≥ | Q m a x | − | Q | + 1 {\displaystyle k\geq {|Q_{max}|}-{|Q|}+1} ) are added to the back of R as they appear in each C k {\displaystyle C_{k}} and in increasing order with respect to index k {\displaystyle k} . In the ColorSort algorithm, only these vertices are assigned colors C ( v ) = k {\displaystyle C(v)=k} . The pseudocode of the ColorSort algorithm is:

procedure ColorSort(R, C) is max_no := 1; kmin := |Qmax| − |Q| + 1; if kmin ≤ 0 then kmin := 1; j := 0; C1 := Ø; C2 := Ø;

for i := 0 to |R| − 1 do p := R[i]; {the i-th vertex in R} k := 1; while Ck ⋂ Γ(p) ≠ Ø do k := k+1; if k > max_no then max_no := k; Cmax_no+1 := Ø; end if Ck := Ck ⋃ {p}; if k < kmin then R[j] := R[i]; j := j+1; end if end for

C[j−1] := 0;

for k := kmin to max_no do for i := 1 to |Ck| do R[j] := Ck[i]; C[j] := k; j := j+1; end for end for

Example

The graph above can be described as a candidate set of vertices R = {7(5), 1(4), 4(4), 2(3), 3(3), 6(3), 5(2), 8(2)}, and used as input for both the approximate coloring algorithm and the ColorSort algorithm. Either algorithm can be used to construct the following table:

… excerpt ends here. Continue reading the full article.

Illustrations

MaxCliqueDyn algorithm illustration
MaxCliqueDyn algorithm illustration

Worked examples

Example 1 — a first encounter with MaxCliqueDyn algorithm

Start with the simplest possible case. Write down what MaxCliqueDyn algorithm claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, 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 MaxCliqueDyn algorithm 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 MaxCliqueDyn algorithm 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 MaxCliqueDyn algorithm

In research
MaxCliqueDyn algorithm appears in computer science 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 MaxCliqueDyn algorithm 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
MaxCliqueDyn algorithm is common in secondary-school and first-year university syllabi. It links to neighbouring topics Graph algorithms, so understanding it makes those chapters shorter.
In everyday life
Look for MaxCliqueDyn algorithm 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 MaxCliqueDyn algorithm in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what MaxCliqueDyn algorithm 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 MaxCliqueDyn algorithm out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is MaxCliqueDyn algorithm in simple terms?

The MaxCliqueDyn algorithm is an algorithm for finding a maximum clique in an undirected graph. MaxCliqueDyn is based on the MaxClique algorithm, which finds a maximum clique of bounded size.

Why does MaxCliqueDyn algorithm matter?

Because it connects several computer science 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 MaxCliqueDyn algorithm?

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 MaxCliqueDyn algorithm.

Tags

  • Graph algorithms

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