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Operations Research - Jacek Błażewicz bridging gaps between Manufacturing and Biology

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Jacek Błażewicz. Operations Research -. bridging gaps between Manufacturing and Biology. Presentation of our region. Presentation of our region. Presentation of our region. Siegen. Nodes. Arcs. GRAPHS. One of the main concepts used in Computer Science and Operations Research. - PowerPoint PPT Presentation

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Page 1: Operations Research -

Operations Research -

Jacek Błażewicz

bridging gaps between Manufacturing and Biology

Page 2: Operations Research -

Presentation of our region

Page 3: Operations Research -

Presentation of our region

Page 4: Operations Research -

Presentation of our region

Page 5: Operations Research -

Siegen

Page 6: Operations Research -

GRAPHSOne of the main concepts used in Computer Science and Operations Research.

Nodes

Arcs

Used to present different processes.

Page 7: Operations Research -

Poznań

Jacek Błażewicz

Jan Węglarz

`

Page 8: Operations Research -

Poznań

Siegen

Erwin Pesch

Page 9: Operations Research -

Poznań

Siegen Clausthal-Zellerfeld

Klaus Ecker

Page 10: Operations Research -

Poznań

Siegen

Saarbrücken

Clausthal-Zellerfeld

Günter Schmidt

Page 11: Operations Research -
Page 12: Operations Research -

Poznań

Siegen

Jacek BłażewiczMałgorzata Sterna

Erwin Pesch

Page 13: Operations Research -

Poznań

Siegen

Redmond

Page 14: Operations Research -

Poznań

Siegen

Redmond

Livermore

Page 15: Operations Research -

Jacek Błażewicz

Erwin Pesch

Poznań

Siegen

Redmond

Livermore

Page 16: Operations Research -

Bartosz

NowierskiŁukasz

Szajkowski

Bartosz

Nowierski

Łukasz

Szajkowski

Bartosz Nowierski

Łukasz Szajkowski

Poznań

Siegen

Redmond

Livermore

Jacek Błażewicz

Erwin Pesch

Page 17: Operations Research -

FLEXIBLE MANUFACTURING SYSTEM

Page 18: Operations Research -

HPC CENTER in POZMAN

Page 19: Operations Research -

Scheduling problems (deterministic)

1. A set of m processorsP1 , P2 , ... , Pm

2. A set of n tasksT1 , T2 , ... , Tn

3. Each task is characterized by

- processing time - pj

4. Precedence constraints Ti Tj

Page 20: Operations Research -

5. Preemptions

6. Criterion

- Cmax = max{Cj}

t

P1

P2

Tj

Tk

0 Cj Cmax

Tj

Tl

Page 21: Operations Research -

Partial order Ti Tj

Types of precedence graphs

Independent tasks

Dependent tasks task – on – node

chains

 in-trees opposing forest

 out-trees

Ti Tj

Page 22: Operations Research -

general graphs

  task – on - arc

uniconnected activity network

 

uan

1

2

4

3

T1 T4

T3T2

T5

Page 23: Operations Research -

Pm│pmtn,uan │Cmax

 a) 

1

2

4

3

T1 T4

T3

T5

T2

Uniquely ordered event nodes.

Page 24: Operations Research -

b)        

An example of a simple uniconnected activity network (a) and the corresponding precedence graph (b).

T1 T4

T3

T2 T5

Page 25: Operations Research -

Now LP formulation:

  Minimize

Subject to   

j=1,2,...,n xj ≥ 0

 Complexity K = O(nm) - a number of variables, thus for a fixed m the problem can be solved in polynomial time [Khachiyan, Karmarkar]. [J.Błażewicz, W.Cellary, R.Słowiński, J.Węglarz, 77]

K

1iimax xC

px ji

i

Qj

Page 26: Operations Research -

In practice:

Polynomial time = easy(solvable in practice)

NP-hard = difficult(not solvable in practice)

Page 27: Operations Research -

Theorem 1

Let G be an activity network (task-on-arcgraph). G is uniconnected if and only if G has aHamiltonian path.

Page 28: Operations Research -

Original graph G HamiltonianPrecedence graph H ?

Page 29: Operations Research -

Molecular biology

Chemical foundations of life Information coded in chemical molecules

Computational biology

Page 30: Operations Research -

Met

hod

s Met

hod

sPro

blem

s Pro

blem

s

Operations Research

Molecular Biology

Page 31: Operations Research -
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DNA recognition

Human genome pairs of bases 3% nucleotides coding an information

9103

Page 34: Operations Research -
Page 35: Operations Research -

Human genome 3000 books

(valid information 90 books)

1 cell bacteria 20 books

Some flies 5000 books

Page 36: Operations Research -

Analyzed structures

One dimensional structures Analysis of DNA chains (and an information they carry on)

Two dimensional structures Analysis (and recognition) of substructures formed by consecutive subchains (e.g. Α-helix, β-harmony)

Three dimensional structures Analysis of 3-dimensional helix (NMR experiment)

A C G A T G C AG . . . . .

Page 37: Operations Research -

One dimensional structures

1.Reading DNA chains

2.Understanding an information contained in DNA

sequence alignment finding motifs in sequences assigning functions to subsequences (or motifs)

Page 38: Operations Research -

Levels

Sequencing

up to 700 nucleotides

combinatorial exact methods

Assembling

up to 1000000 nucleotides

heuristics

Mapping

greater than 1000000 nucleotides

search in data bases

Page 39: Operations Research -

CGGACACCGACGTCATTCTCATGTGCTTCTCGGCACA

Chromosome

Clones

Sequencing

(works on 103-104 bp range)

Assembling

(works on 105-106 bp range)

Genetic linkage map

(works on 107-108 bp range)

The different scales at which the human genome is studied

Page 40: Operations Research -

Hybridization Experiment

A C G T A C G T A C G T A C G T

Round 1

Round 2

A AC

ACG

ACGT

A A C A C G A C G T

1. Making a DNA chip

Page 41: Operations Research -

Round 3

A C G TACGT

A A A A

... and so on ... DNA chip

Full libraryof tetranucleotides

0,4mm

0,4mm 25m site per probe

44 – 0.0016 cm2

48 – 0.4096 cm2

410 – 6.5536 cm2

AAAA AACA AAGAAAAC AACC AAGCAAAT AACG AAGGAAAT AACT AAGTACAA ACCA

Page 42: Operations Research -

DNA chip TCCACTG... Many labeled copies of an original sequence

. .. . . . .

spectrum

Hybridization Experiment –cont.

2. Hybridization reaction

3. Reading results

Fluorescence image of the chip

Spectrum – a set of oligonucleotides complementary to fragments of original sequence

Page 43: Operations Research -

A hybridization reaction between a probe of known sequence (l-mer) and an unknown sequence (n-mer):

n-mer - . . . A A C T A G A C C T . . .

l-mer - G A T

C T A

A sequence complementary to the probe exists in the target

Page 44: Operations Research -

DNA sequencing without errors

The original sequence: AACTAGACCT

Spectrum = {AAC,ACT,CTA,TAG,AGA,GAC,ACC,CCT}

(Two possible solutions: AACTAGACCT, AACCTAGACT)

Lysov (1988)

A graph is based on l-mers (graph H)

Finding a Hamiltonian path – NP-hard

AAC

CCT

ACTCTA

TAG

ACC GACAGA

Page 45: Operations Research -

Pevzner (1989)

AAC AA AC

A graph based on (l-1)-mers (graph G):

AAAC

CT

TA

CC GAAG

Finding an Eulerian path – polynomially solvable

A problem of equivalence

A problem of uniqueness

Page 46: Operations Research -

Equivalence problem

The above class of directed labeled graphs –DNA graphs.

Characterization and recognition of these graphs and finding conditions for which the above transformation is possible.

J.Błażewicz, A.Hertz, D.Kobler, D.de Werra, On some properties of DNA graphs, Discrete Applied Math., 1999.

Page 47: Operations Research -

Definition

The directed line graph H = (V,U) of graph G = (X,V) is the graph with vertex set V and such that there is an arc from vertex x to vertex y in H if and only if the terminal endpoint of arc x in G is the initial endpoint of arc y in G.

Graph G – Pevzner graph

Directed line graph H – Lysov graph

Page 48: Operations Research -

Theorem 2

Let H be the directed line-graph of a graph G. Then

there is an Eulerian path in G if and only if there is a

Hamiltonian path in H.

Page 49: Operations Research -

Back to scheduling.

Original graph G Hamiltonian

Its directed line-graph H ?

Page 50: Operations Research -

J.Błażewicz, D.Kobler

European Journal of Operational Research, 2002

Theorem 3

Original graph G uan Hamiltonian

Its directed line-graph H interval order.

Page 51: Operations Research -

AB

CD

A B

C D

Intervals

Interval order (graph)

Page 52: Operations Research -

Theorem 4

Pm | pmtn, interval order | Cmax

is solvable in polynomial time.

Page 53: Operations Research -

Ich danke Ihnen ganz herzlich für diese hohe und besondere Auszeichnung. Ich freue mich darüber sehr und hoffe, dass die bestehende sehr gute Zusammenarbeit in der Zukunft noch weiter intensiviert wird.

Diese Auszeichnung ist dann sicherlich ein weiterer Anreiz.