A guide to algorithm design: paradigms, methods, and complexity analysis
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| Format: | Buch |
| Sprache: | Englisch |
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Boca Raton [u.a.]
CRC Press
2014
|
| Schriftenreihe: | Chapman & Hall/CRC applied algorithms and data structures series
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| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025775845&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XVII, 362 S. 24 cm |
| ISBN: | 9781439825648 |
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| 001 | BV040795638 | ||
| 003 | DE-604 | ||
| 005 | 20140311 | ||
| 007 | t| | ||
| 008 | 130305s2014 xx |||| 00||| eng d | ||
| 020 | |a 9781439825648 |c hbk |9 978-1-4398-2564-8 | ||
| 035 | |a (OCoLC)859367586 | ||
| 035 | |a (DE-599)HBZHT017051379 | ||
| 040 | |a DE-604 |b ger | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-473 |a DE-703 |a DE-355 |a DE-91G |a DE-83 | ||
| 084 | |a ST 134 |0 (DE-625)143590: |2 rvk | ||
| 084 | |a DAT 530f |2 stub | ||
| 100 | 1 | |a Benoit, Anne |e Verfasser |0 (DE-588)1042919720 |4 aut | |
| 245 | 1 | 0 | |a A guide to algorithm design |b paradigms, methods, and complexity analysis |c Anne Benoit, Yves Robert and Frédéric Vivien |
| 264 | 1 | |a Boca Raton [u.a.] |b CRC Press |c 2014 | |
| 300 | |a XVII, 362 S. |c 24 cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Chapman & Hall/CRC applied algorithms and data structures series | |
| 650 | 0 | 7 | |a Datenstruktur |0 (DE-588)4011146-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Computer |0 (DE-588)4070083-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Algorithmus |0 (DE-588)4001183-5 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Computer |0 (DE-588)4070083-5 |D s |
| 689 | 0 | 1 | |a Algorithmus |0 (DE-588)4001183-5 |D s |
| 689 | 0 | |5 DE-604 | |
| 689 | 1 | 0 | |a Algorithmus |0 (DE-588)4001183-5 |D s |
| 689 | 1 | 1 | |a Datenstruktur |0 (DE-588)4011146-5 |D s |
| 689 | 1 | |5 DE-604 | |
| 700 | 1 | |a Robert, Yves |d 1938- |e Verfasser |0 (DE-588)1042919046 |4 aut | |
| 700 | 1 | |a Vivien, Frédéric |e Verfasser |4 aut | |
| 856 | 4 | 2 | |m Digitalisierung UB Bamberg - ADAM Catalogue Enrichment |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025775845&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-025775845 | |
Datensatz im Suchindex
| DE-BY-TUM_call_number | 0102 DAT 530f 2014 A 205 |
|---|---|
| DE-BY-TUM_katkey | 1967505 |
| DE-BY-TUM_location | 01 |
| DE-BY-TUM_media_number | 040080393793 |
| _version_ | 1821933590654484480 |
| adam_text | Contents
Preface
xv
I Polynomial-
1
irne
algorithms: Exercises
1
1
Introduction to complexity
3
1.1
On the complexity to
computo
.r
...............
Λ
1.1.1
Naive method
....................... 4
1.1.2
Binary method
...................... 4
1.1.
Λ
Factorization method
.................. 4
1.1.4
Knuth s tree method
...................
Гі
1.1.
Γ)
Complexity results
....................
(i
1.2
Asymptotic notations:
Ο. ο, Θ,
and
Ω
.............
S
1.. ?
Exercises
............................. 8
Exorcise
1.1:
Longest
balancée}
section
............. 8
Exorcise
1.2:
Find the star
.................... 9
Exorcist4
1.3:
Breaking boxes
.................. 9
Exercise
1.4:
Maximum of
η
integers
.............. 10
Exercise
1.5:
Maximum and minimum of
η
integers
...... 10
Exercise4
1.6:
Maximum and second maximum of
η
integers
. 11
Exercise
1.7:
Merging two sorted sets
.............. 11
Exercise
1.8:
The toolbox
.................... 12
Exercise
1.9:
Sorting a small number of objects
........ 12
1.4
Solutions to exercises
...................... 14
Solution to Exercise
1.1:
Longest balanced section
...... 14
Solution to Exercise
1.2:
Find the star
............. 15
Solution to Exercise
1.3:
Breaking boxes
............ 16
Solution to Exercise
1.4:
Maximum of
η
integers
....... 17
Solution to Exercise
1.5:
Maximum and minimum of
η
integers
20
Solution to Exercise
1.6:
Maximum and second maximum of
η
integers
.......................... 23
Solution to Exercise
1.7:
Merging two sorted sets
....... 25
Solution to Exercise
1.8:
The toolbox
............. 26
Solution to Exercise
1.9:
Sorting a small number of objects
. 29
1.5
Bibliographical notes
...................... 31
VI
2
Divide-and-conquer
33
2.1
St
rassen
Ή
algorithm
....................... 33
2.2
Master theorem
......................... 36
2.3
Solving recurrences
....................... 37
2.3.1
Solving homogeneous recurrences
............ 37
2.3.2
Solving nonhoniogeneous recurrences
.......... 38
2.3.3
Solving the recurrence for Strassen s algorithm
.... 39
2.4
Exercises
............................. 39
Exorcise
2.1:
Product of two polynomials
........... 39
Exercise
2.2:
Toeplitz matrices
................. 40
Exorcise
2.3:
Maximum sum
................... 40
Exercise
2.4:
Boolean matrices: The Four-Russians algorithm
41
Exorcise
2.5:
Matrix multiplication and inversion
....... 42
2.5
Solutions to exorcises
...................... 42
Solution to Exercise
2.1:
Product of two polynomials
..... 42
Solution to Exercise
2.2:
Toeplitz matrices
........... 44
Solution to Exercise
2.3:
Maximum sum
............ 45
Solution to Exercise
2.4:
Boolean matrices:
Tlu1
Four-Russians
algorithm
......................... 49
Solution to Exorcise
2.5:
Matrix multiplication and inversion
50
2.0
Bibliographical notes
...................... 51
3
Greedy algorithms
53
3.1
Motivating example:
Тік1
sports hall
.............. 53
3.2
Designing greedy algorithms
.................. 55
3.3
Graph coloring
.......................... 56
3.3.1
On coloring bipartite graphs
.............. 56
3.3.2
Greedy algorithms to color general graphs
....... 57
3.3.3
Coloring interval graphs
................. 60
3.4
Theory of matroids
....................... 61
3.5
Exercises
............................. 64
Exercise
3.1:
Interval cover
................... 64
Exercise
3.2:
Memory usage
................... 64
Exercise
3.3:
Scheduling dependent tasks on several machines
65
Exercise
3.4:
Scheduling independent tasks with priorities
. . 66
Exercise
3.5:
Scheduling independent tasks with deadlines
. . 66
Exercise
3.6:
Edge matroids
................... 67
Exercise
3.7:
Huffman code
................... 67
3.6
Solutions to exercises
...................... 68
Solution to Exercise
3.1:
Interval cover
............. 68
Solution to Exercise
3.2:
Memory usage
............ 69
Solution to Exercise
3.3:
Scheduling dependent tasks on several
machines
......................... 71
Solution to Exercise
3.4:
Scheduling independent tasks with
priorities
......................... 72
Vil
Solution
to Exercise
3.5:
Scheduling independent tasks with
deadlines
......................... 73
Solution to Exercise
3.6:
Edge matroids
............ 74
Solution to Exercise
3.7:
Huffman code
............. 75
3.7
Bibliographical notes
...................... 79
4
Dynamic programming
81
4.1
The coin changing problem
................... 81
4.2
The knapsack problem
..................... 84
4.3
Designing dynamic-programming algorithms
......... 86
4.4
Exercises
............................. 87
Exercise
4.1:
Matrix chains
................... 87
Exercise»
4.2:
Тік1
library
..................... 88
Exercise
4.3:
Polygon
triangulation
............... 88
Exercise
4.4:
Sentare
of ones
................... 89
Exercise*
4.5:
The wind band
.................. 89
Exercise
4.
fi: Ski
rental
...................... 89
Exercise
4.7:
Building set
.................... 90
4.5
Solutions to exercises
...................... 90
Solution to Exercise
4.1:
Matrix chains
............. 90
Solution to Exercise
4.2:
The library
.............. 91
Solution to Exercise
4.3:
Polygon
triangulation
........ 93
Solution to Exercise
4.4:
Square
oť
ones
............ 90
Solution to Exercise
4.5:
The wind band
............ 98
Solution to Exercise
4.6:
Ski rental
............... 98
Solution to Exercise
4.7:
Building set
.............. 102
4.0
Bibliographical note s
...................... 103
5
Amortized analysis
105
5.1
Methods for amortized analysis
................. 105
5.1.1
Running examples
.................... 1(35
5.1.2
Aggregate analysis
.................... 106
5.1.3
Accounting method
................... 106
5.1.4
Potential method
..................... 107
5.2
Exercises
............................. 108
Exercise1
5.1:
Binary counter
................... 108
Exercise
5.2:
Inserting and deleting
............... 108
Exercise
5.3:
Stack
........................ 109
Exercise
5.4:
Deleting half the elements
............ 109
■*·<->
Exercise
5.5:
Searching and inserting
.............. 109
Exercise1
5.6:
Splay trees
..................... 110
Exercise?
5.7:
Half perimeter of a polygon
........... 112
5.3
Solutions to exercises
...................... 112
Solution to Exercise
5.1:
Binary counter
............ 112
Solution to Exercise
5.2:
Inserting and deleting
........ 113
Vlil
Solution to Exercise
Γ). Λ:
Stack
................. 11-4
Solution to Exercise
5.4:
Deleting half
t
lit1 elements
...... 11
Γ»
Sohlt
іон
to Exercise
5.5:
Searching and inserting
.......
lib
Solution to Exercise1 5.(i: Splay trees
.............. 117
Solution to Exercise
5.7:
Halí
perimeter of a polygon
..... 119
5.4
Bibliographical notes
...................... 122
II NP-completeiiess and beyond
123
6
NP-completeness
125
(i.l A practical approach to complexity theory
.......... 125
(І.2
Problem classes
.........................
12(i
0.2.1
Problems in
Ρ
...................... 127
(і.
2.2
Problems in
XP
.....................
12í)
(і.
3
NP-complete problems and reduction theory
......... 132
(i.3.1 Polynomial reduction
.................. 132
ίί.3.2
Cook s theorem
......................
ПУЛ
(і. Л. Л
Growing
t
he class NPC of XP-complete problems
. . . 134
ii.
ΛΛ
Optimization problems versus decision problems
. . . 135
(i.l Examples
oí
NP-coinplete problems and reductions
.....
J
3(>
П.4.Ј з-ЅАТ
...........................
їла
(і.
4.2
CLIQUE
.........................
13N
(і.
4.3
VERTEX-COVER
.................... 139
(і.
4.4
Scheduling problems
................... 140
6.4.5
Other famous NP-complete j)rol)lems
.......... 142
(i.5 Importance of problem
flefíiiitioii
................ 14,4
í).(í
Strong NP-coinpIeteness
.................... 145
(¡.7
Why does it matter?
......................
14(i
(>.8 Bibliographical notes
......................
14(i
7
Exercises on NP-completeness
149
7.1
Easy reductions
......................... 149
Exercise
7.1:
Wheel
....................... 149
Exercise
7.2:
Knights of the round table
............ 149
Exercise
7.3:
Variants of CLIQUE
............... 149
Exercise
7.4:
Path with vertex pairs
.............. 150
Exercise
7.5:
VERTEX-COVER with even degrees
...... 150
Exercise
7.6:
Around
2-
PARTITION
.............. 150
7.2
About graph coloring
...................... 151
Exercise
7.7:
COLOR
....................... 151
Exercise
7.8:
S-COLOR
...................... 151
Exercise
7.9:
S-COLOR-PLAN
................. 152
7.3
Scheduling problems
....................... 152
Exercise
7.10:
Scheduling independent tasks with
p
processors
152
8
їх
Exercise
7.11:
Scheduling with two processors
......... 152
7.4
More involved reductions
.................... 153
Exercise
7.12:
Transitive subchain
............... 153
Exercise
7.13:
INDEPENDENT SET
.............. 153
Exercise
7.14:
DOMINATING SET
............... 153
Exercise
7.15:
Carpenter
..................... 153
Exercise
7.16:
fc-center
...................... 153
Exercise
7.17:
Variants of 3-SAT
................ 154
Exercise
7.18:
Variants of SAT
................. 154
7.5 2-
PARTITION is NP-complete
................. 155
Exercise
7.19:
SUBSET-SUM
.................. 155
Exercise
7.20:
NP-completenoss of
2-
PARTITION
...... 155
7.
β
Solutions to exercises
...................... 155
Solution to Exorcise
7.1:
Wheel
................. 150
Solution to Exercise
7.2:
Knights of the round table
..... 150
Solution to Exercise
7.3:
Variants of CLIQUE
......... 157
Solution to Exorcise
7.4:
Path with vertex pairs
........ 158
Solution to Exercise
7.5:
VERTEX-COVER with oven degrees
158
Solution to Exorcise
7.0:
Around 2-PARTITION
....... 159
Solution to Exercise
7.7:
COLOR
................ 100
Solution to Exercise
7.8:
3-COLOR
............... 162
Solution to Exercise
7.9:
3-COLOR-PLAN
........... 163
Solution to Exercise
7.10:
Scheduling independent tasks with
ρ
processors
........................ 100
Solution to Exercise
7.11:
Scheduling with two processors
. . 100
Solution to Exercise
7.12:
Transitive subchain
......... 107
Solution to Exercise
7.13:
INDEPENDENT SET
....... 108
Solution to Exercise
7.14:
DOMINATING SET
........ 109
Solution to Exercise
7.15:
Carpenter
.............. 170
Solution to Exercise
7.16:
/c-center
............... 171
Solution to Exercise
7.17:
Variants of 3-SAT
.......... 172
Solution to Exercise
7.18:
Variants of SAT
........... 174
Solution to Exercise
7.19:
SUBSET-SUM
........... 175
Solution to Exercise
7.20:
NP-completeness of 2-PARTITION
177
7.7
Bibliographical notes
...................... 178
Beyond NP-completeness
179
8.1
Approximation results
...................... 179
8.1.1
Approximation algorithms
................ 180
8.1.2
Vertex cover
....................... 181
8.1.3
Traveling salesman problem (TSP)
........... 182
8.1.4
Bin packing
........................ 183
8.1.5
2-PARTITION
...................... 187
8.2
Polynomial problem instances
................. 192
8.2.1
Partitioning problems
.................. 193
χ
S.
2.2
Assessing
prob
loin complexity
..............
ïi)-i
8.3
Linear programming
.......................
l·^·1
5.
3.1
Formal definition
.....................
Н)5
5.
3.2
Relaxation
and rounding
................. 19
8.4
Randomized algorithms
..................... 200
5.
4.1
The algorithm
......................
2(>1
8.4.2
Results
.......................... 201
8.5
Branch-and-bound and backtracking
.............. 202
8.5.1
Backtracking: The
η
queens
............... 203
8.
Γ),
2
Branch-and-bound: The knapsack
........... 204
8.5.3
Graph algorithms
..................... 200
8.Ѓ)
Bibliographical notes
...................... 209
9
Exercises going beyond NP-completeness
211
9.1
Approximation results
...................... 211
Exercise
9. 1:
Single machine scheduling
............ 211
Exercise
9.2:
SUBSET-SUM
................... 212
Exercise
9.3:
SET-COVER
.................... 213
Exercise!).!: VERTEX-COVER
................ 213
Exercise
Ił.
Гг.
Scheduling independent tasks in parallel
.... 215
Exercise1
ÍJ.ŕi:
Point clustering
.................. 215
Exercise I).
7:
A-center
...................... 2
Hi
Exercise
9.8:
Knapsack
...................... 217
9.2
Dealing with NP-complete problems
.............. 218
Exercise
í).!):
Mixed integer linear program for replica place¬
ment
............................ 218
Exercise
9.10:
A randomized algorithm for independent set
. 218
Exercise
9.11:
Braneh-and-bound applied to MAX-SAT
. . . 219
9.3
Solutions to exercises
...................... 219
Solution to Exercise
9.1:
Single machine scheduling
...... 219
Solution to Exercise
9.2:
SUBSET-SUM
............ 221
Solution to Exercise
9.3:
SET-COVER
............. 223
Solution to Exercise
9.4:
VERTEX-COVER
.......... 224
Solution to Exercise
9.5:
Scheduling independent tasks in par¬
allel
............................ 226
Solution to Exercise
9.6:
Point clustering
........... 228
Solution to Exercise
9.7:
^-center
................ 229
Solution to Exercise
9.8:
Knapsack
............... 231
Solution to Exercise
9.9:
Mixed integer linear program for
replica placement
..................... 234
Solution to Exercise
9.10:
A randomized algorithm for inde¬
pendent set
........................ 237
Solution to Exercise
9.11:
Branch-and-bound applied to MAX-
SAT
............................ 237
9.4
Bibliographical notes
...................... 238
Xl
III Reasoning on problem complexity
239
10
Reasoning to assess a problem complexity
241
10.1
Basic reasoning
......................... 241
10.1.1
Polynomial instances
................... 241
10.1.2
XP-complete instances
.................. 242
10.2
Set of problems with polynomial-time algorithms
....... 243
10.3
Set of NP-complete problems
.................. 244
10.3.1
Numbers
......................... 245
10.3.2
Graphs
.......................... 246
11
Chains-on-chains partitioning
249
11.1
Optimal algorithms for homogeneous resources
........ 249
11.1.1
Dynamic-programming algorithm
............ 250
11.1.2
Binary search algorithm
................. 250
11.1.3
Improved algorithms
................... 250
11.2
Variants of
t
ho problem
..................... 252
11.2.1
Communication costs
.................. 252
11.2.2
Chain of heterogeneous resources
............ 253
11.3
Extension to
n
clique of heterogeneous resources
....... 254
11.3.1
NP-coinplotonoss
..................... 254
11.3.2
Practical solutions
.................... 257
11.3.3
Integer linear program
.................. 257
11.4
Conclusion
............................ 258
12
Replica placement in tree networks
261
12.1
Access policies
.......................... 262
12.1.1
Motivation
........................ 262
12.1.2
Impact of the policies on the existence of a solution
. 263
12.1.3
Impact of the policies on the cost of a solution
.... 264
12.2
Complexity results
........................ 206
12.2.1
Definitions
........................ 266
12.2.2
MinNb problem
..................... 267
12.2.3
MIXCOST problem
.................... 273
12.2.4
Integer linear program
.................. 275
12.3
Variants of the replica placement problem
........... 279
12.3.1
Enforcing a quality of service
.............. 280
12.3.2
Power-aware replica placement
............. 282
12.4
Conclusion
............................ 286
13
Packet routing
287
13.1
MEDP: Maximum edge-disjoint paths
............ 288
13.1.1
Problem statement
.................... 288
13.1.2
Naive greedy algorithm
................. 289
13.1.3
Short-requests-first greedy algorithm
.......... 291
Xli
l i.
1.4
Inapproxhiiability
result
..................
2Í)2
13.2
PRVP:
Packet
routing; with variable-paths
.......... 204
13.2.1
Problem statement
.................... 294
13.2.2
Bounding optimal nmkespan via linear programming
-
2íí5
13.2.3
Routing algorithm
.................... 207
13.2.4
Steady-state approach
.................. 300
13.3
Conclusion
............................ 301
14
Matrix product, or tiling the unit square
303
14.1
Problem motivation
....................... 304
14.2
XP-coinpleteness
......................... 307
14.3
A guaranteed heuristic
..................... 31
J
14.3.1
The
ColPkhiSí m(,s·)
problem
............. 312
14.3.2
Performance guarantee
..................
3Hi
14.3.3
Looking for a better solution
.............. 317
14.4
Related problems
........................ 320
15
Online scheduling
321
15.1
Flow time optimization
..................... 322
15.2
Competitive analysis
...................... 324
15.2.1
Definition
......................... 324
15.2.2
Method to establish a competitive analysis result
. . . 327
15.3 Makespan
optimization
..................... 334
15.3.1
List scheduling algorithms
................ 335
15.3.2
Randomized optimization of niakespan
.........
33S
15.4
Conclusion
............................ 347
References
349
Index
359
|
| any_adam_object | 1 |
| author | Benoit, Anne Robert, Yves 1938- Vivien, Frédéric |
| author_GND | (DE-588)1042919720 (DE-588)1042919046 |
| author_facet | Benoit, Anne Robert, Yves 1938- Vivien, Frédéric |
| author_role | aut aut aut |
| author_sort | Benoit, Anne |
| author_variant | a b ab y r yr f v fv |
| building | Verbundindex |
| bvnumber | BV040795638 |
| classification_rvk | ST 134 |
| classification_tum | DAT 530f |
| ctrlnum | (OCoLC)859367586 (DE-599)HBZHT017051379 |
| discipline | Informatik |
| format | Book |
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| id | DE-604.BV040795638 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T16:25:51Z |
| institution | BVB |
| isbn | 9781439825648 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-025775845 |
| oclc_num | 859367586 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG DE-703 DE-355 DE-BY-UBR DE-91G DE-BY-TUM DE-83 |
| owner_facet | DE-473 DE-BY-UBG DE-703 DE-355 DE-BY-UBR DE-91G DE-BY-TUM DE-83 |
| physical | XVII, 362 S. 24 cm |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| publisher | CRC Press |
| record_format | marc |
| series2 | Chapman & Hall/CRC applied algorithms and data structures series |
| spellingShingle | Benoit, Anne Robert, Yves 1938- Vivien, Frédéric A guide to algorithm design paradigms, methods, and complexity analysis Datenstruktur (DE-588)4011146-5 gnd Computer (DE-588)4070083-5 gnd Algorithmus (DE-588)4001183-5 gnd |
| subject_GND | (DE-588)4011146-5 (DE-588)4070083-5 (DE-588)4001183-5 |
| title | A guide to algorithm design paradigms, methods, and complexity analysis |
| title_auth | A guide to algorithm design paradigms, methods, and complexity analysis |
| title_exact_search | A guide to algorithm design paradigms, methods, and complexity analysis |
| title_full | A guide to algorithm design paradigms, methods, and complexity analysis Anne Benoit, Yves Robert and Frédéric Vivien |
| title_fullStr | A guide to algorithm design paradigms, methods, and complexity analysis Anne Benoit, Yves Robert and Frédéric Vivien |
| title_full_unstemmed | A guide to algorithm design paradigms, methods, and complexity analysis Anne Benoit, Yves Robert and Frédéric Vivien |
| title_short | A guide to algorithm design |
| title_sort | a guide to algorithm design paradigms methods and complexity analysis |
| title_sub | paradigms, methods, and complexity analysis |
| topic | Datenstruktur (DE-588)4011146-5 gnd Computer (DE-588)4070083-5 gnd Algorithmus (DE-588)4001183-5 gnd |
| topic_facet | Datenstruktur Computer Algorithmus |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025775845&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT benoitanne aguidetoalgorithmdesignparadigmsmethodsandcomplexityanalysis AT robertyves aguidetoalgorithmdesignparadigmsmethodsandcomplexityanalysis AT vivienfrederic aguidetoalgorithmdesignparadigmsmethodsandcomplexityanalysis |
Inhaltsverzeichnis
Paper/Kapitel scannen lassen
Paper/Kapitel scannen lassen
Teilbibliothek Mathematik & Informatik
| Signatur: |
0102 DAT 530f 2014 A 205 Lageplan |
|---|---|
| Exemplar 1 | Ausleihbar Am Standort |