Scheduling Algorithms

By: Peter Brucker

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Paperback | 6 February 2007 | Edition Number 5

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384 Pages

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Revised

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23.5 x 15.5 x 2.54

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Besides scheduling problems for single and parallel machines and shop scheduling problems, this book covers advanced models involving due-dates, sequence dependent changeover times and batching. Discussion also extends to multiprocessor task scheduling and problems with multi-purpose machines. Among the methods used to solve these problems are linear programming, dynamic programming, branch-and-bound algorithms, and local search heuristics. The text goes on to summarize complexity results for different classes of deterministic scheduling problems.

Industry Reviews

From the reviews of the fourth edition:

"This is a book about scheduling algorithms. ... The book contains eleven chapters. ... Most of the chapters contain the summarized complexity results. In this edition the complexity columns have been updated. The book is completed by the bibliography which also has been updated and now contains 198 references. The book is well organized. It will be useful for specialists in scheduling theory and in combinatorial optimization." (I.N. Lushchakova, Zentralblatt MATH, Vol. 1060, 2005)

From the reviews of the fifth edition:

"One of the competitive books on the theory of machine scheduling in the market, this book, now in its fifth edition, was first published in 1995. ... This book is theoretically oriented with little treatment of practical issues. It is suitable for researchers and graduate students in mathematics, computer science, operations research, management science, and industrial engineering. ... To summarize, this is an excellent theoretically oriented reference book written by an expert on the classical results of deterministic machine scheduling." (Donglei Du, SIAM Review, Vol. 50 (1), 2008)

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Published: 15th October 2010

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Preface	p. v
Classification of Scheduling Problems	p. 1
Scheduling Problems	p. 1
Job Data	p. 2
Job Characteristics	p. 3
Machine Environment	p. 5
Optimality Criteria	p. 6
Examples	p. 7
Some Problems in Combinatorial Optimization	p. 11
Linearand Integer Programming	p. 11
Transshipment Problems	p. 12
The Maximum Flow Problem	p. 13
Bipartite Matching Problems	p. 14
The Assignment Problem	p. 18
Arc Coloring of Bipartite Graphs	p. 22
Shortest Path Problems and Dynamic Programming	p. 26
Computational Complexity	p. 37
The Classes <$>{cal P}<$> and <$>{cal N}{cal P}<$>	p. 37
<$>{cal N}{cal P}<$>-complete and <$>{cal N}{cal P}<$>-hard Problems	p. 41
Simple Reductions Between Scheduling Problems	p. 48
Living with <$>{cal N}{cal P}<$>-hard Problems	p. 51
Local Search Techniques	p. 51
Branch-and-Bound Algorithms	p. 56
Single Machine Scheduling Problems	p. 61
Minimax Criteria	p. 62
Lawler's Algorithm for 1 prec f_max	p. 62
1	p. rec; p<s
Maximum Lateness and Related Criteria	p. 67
Total Weighted Completion Time	p. 73
1 tree <$>sum<$>w_jC_j	p. 73
1 sp-graph <$>sum<$>w_jC_j	p. 79
Weighted Number of Late Jobs	p. 84
1 r_j; p_j = 1 <$>sum<$>w_jU_j	p. 84
1 p_j = 1 <$>sum<$>w_jU_j	p. 85
1 <$>sum<$>U_j	p. 86
1 r_j; pmtn <$>sum<$>w_jU_j	p. 88
Total Weighted Tardiness	p. 93
Problems with Release Times and Identical Processing Times	p. 98
1 r_j; p_j = p <$>sum<$>w_jU_j	p. 98
1 r_j; p_j = p <$>sum<$>w_jC_j and 1 r_j; p_j = p <$>sum<$>T_j	p. 101
Complexity of Single Machine Problems	p. 104
Parallel Machines	p. 107
Independent Jobs	p. 107
Identical Machines	p. 107
Uniform Machines	p. 124
Unrelated Machines	p. 136
Jobs with Precedence Constraints	p. 139
P tree; p_i = 1 L_max-Problems	p. 140
Problem P2 prec; p_i = 1 L_max	p. 145
Complexity Results	p. 150
Shop Scheduling Problems	p. 155
The Disjunctive Graph Model	p. 156
Open Shop Problems	p. 158
Arbitrary Processing Times	p. 158
Unit Processing Times	p. 161
Flow Shop Problems	p. 174
Minimizing Makespan	p. 174
Job Shop Problems	p. 178
Problems with Two Machines	p. 179
Problems with Two Jobs.A Geometric Approach	p. 186
Job Shop Problemswith Two Machines	p. 196
A Branch-and-Bound Algorithm	p. 202
Applying Tabu-Search to the Job Shop Problem	p. 221
Mixed Shop Problems	p. 226
Problemswith Two Machines	p. 226
Problemswith Two Jobs	p. 227
Complexityof Shop Scheduling Problems	p. 232
Due-Date Scheduling	p. 243
Problem 1 d_opt <$>sum<$>w_i L_(i) + w₀ ċ d	p. 244
Problem 1
Problem 1	p. 249
Problem 1	p. 255
Problem 1	p. 257
Problem 1	p. 259
Problem 1	p. 262
Batching Problems	p. 267
Single Machine s-Batching Problems	p. 267
Single Machine p-Batching Problems	p. 271
The Unbounded Model	p. 272
The Bounded Model	p. 276
Complexity Results for Single Machine Batching Problems	p. 277
Changeover Times and Transportation Times	p. 281
Single Machine Problems	p. 282
Problems with Parallel Machines	p. 286
General Shop Problems	p. 290
Multi-Purpose Machines	p. 293
MPM Problems with Identical and Uniform Machines	p. 294
MPM Problems with Shop Characteristics	p. 300
Arbitrary Processing Times	p. 300
Unit Processing Times	p. 311
Complexity Results	p. 315
Multiprocessor Tasks	p. 317
Multiprocessor Task Systems	p. 318
Shop Problems with MPT: Arbitrary Processing Times	p. 323
Shop Problems with MPT: Unit Processing Times	p. 329
Multi-Mode Multiprocessor-Task Scheduling Problems	p. 335
Complexity Results	p. 342
Bibliography	p. 347
Index	p. 367
Table of Contents provided by Publisher. All Rights Reserved.

Scheduling Algorithms

At a Glance

Paperback

Industry Reviews

Shipping

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Defective items

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