Scheduling of Resource-Constrained Projects

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Springer Science & Business Media, 2000 - Business & Economics - 369 pages
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Project management has become a widespread instrument enabling organizations to efficiently master the challenges of steadily shortening product life cycles, global markets and decreasing profit margins. With projects increasing in size and complexity, their planning and control represents one of the most crucial management tasks. This is especially true for scheduling, which is concerned with establishing execution dates for the sub-activities to be performed in order to complete the project. The ability to manage projects where resources must be allocated between concurrent projects or even sub-activities of a single project requires the use of commercial project management software packages. However, the results yielded by the solution procedures included are often rather unsatisfactory. Scheduling of Resource-Constrained Projects develops more efficient procedures, which can easily be integrated into software packages by incorporated programming languages, and thus should be of great interest for practitioners as well as scientists working in the field of project management.
The book is divided into two parts. In Part I, the project management process is described and the management tasks to be accomplished during project planning and control are discussed. This allows for identifying the major scheduling problems arising in the planning process, among which the resource-constrained project scheduling problem is the most important. Part II deals with efficient computer-based procedures for the resource-constrained project scheduling problem and its generalized version. Since both problems are NP-hard, the development of such procedures which yield satisfactory solutions in a reasonable amount of computation time is very challenging, and a number of new and very promising approaches are introduced. This includes heuristic procedures based on priority rules and tabu search as well as lower bound methods and branch and bound procedures which can be applied for computing optimal solutions.
  

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Contents

The Project Management Process
1
12 The Project Life Cycle
2
13 Project Conception
5
131 Feasibility Study
7
132 Economic Analysis
8
133 Risk Analysis
10
134 Project Selection
12
14 Project Definition
15
4314 Precedence Based Bounds
158
432 Destructive Improvement
159
Heuristic Procedures
161
51 Types of Schedules
162
52 PriorityRule Based Methods
167
521 Scheduling Schemes
169
5212 Parallel Scheduling Scheme
171
5213 A Critique of the Scheduling Schemes
173

142 Project Organization
16
143 Process Organization
17
144 Budgeting
19
15 Project Planning
22
152 Scheduling
24
16 Project Execution
26
161 Reporting Monitoring and Control
27
162 Configuration Management
28
163 Quality Management
29
17 Project Termination
30
172 Dissolution
31
Project Planning and Control
33
21 Structuring
34
212 ActivityonNode Networks
37
213 ActivityonArc Networks
41
22 Scheduling
43
222 Slack Time Computations
46
223 Gantt Charts
49
23 Resource Allocation
50
232 ResourceConstrained Scheduling
52
233 TimeConstrained Scheduling
54
24 Control
55
241 Schedule Control
56
242 Cost Control
60
25 Project Management Software
63
251 Features for Project Conception Definition and Termination
64
252 Features for Project Planning
65
253 Features for Project Execution
68
254 General Features
70
ResourceConstrained Scheduling Problems
73
32 Basic Models
76
321 The ResourceConstrained Project Scheduling Problem RCPSP
77
3212 Formulation 1
79
3213 Formulation 2
80
3214 Formulation 3
82
3215 Formulation 4
84
3216 Formulation 5
86
3217 Formulation 6
87
322 The Generalized ResourceConstrained Project Scheduling Problem GRCPSP
89
3221 Properties of GRCPSP
91
3222 Formulations
92
33 Extensions of the Basic Models
95
331 Preemption
96
333 Maximum Time Lags
99
334 State Preserving Jobs
100
335 Further Extensions
102
341 The TimeConstrained Project Scheduling Problem
103
342 The Resource Leveling Problem
104
343 The Resource Investment Problem
105
344 The Net Present Value Problem
106
345 The Weighted Tardiness Problem
108
ResourceConstrained Project Scheduling Solution Methods
111
Lower Bound Methods
113
41 Constructive Lower Bound Methods for RCPSP
114
4112 Bin Packing Bounds
117
4113 Node Packing Bounds
120
4114 Parallel Machine Bounds
124
4115 Precedence Bounds
128
412 Complex Bound Arguments
129
4721 LPRelaxation with Cutting Planes
130
4122 Lagrangean Relaxation
132
4123 Set Covering Based Approach
134
42 Destructive Improvement
136
422 Applying Destructive Improvement to RCPSP
141
4222 Lower Bound Arguments for Contradicting Feasibility
147
43 Lower Bound Methods for GRCPSP
149
431 Simple Bound Arguments
150
4311 Critical Path and Capacity Bounds
152
4312 Node Packing Bounds
153
4313 Parallel Machine Bounds
157
522 Multiple Planning Directions
175
5222 Bidirectional Planning
178
523 Priority Rules
181
524 MultiPass PriorityRule Based Heuristics
187
53 Improvement Methods
190
531 The MetaHeuristic Tabu Search
191
5312 Basic Principles of Tabu Search
193
5313 Extensions of the Basic Approach
196
532 The Tabu Search Procedure RETAPS
198
5322 Tabu Management and Diversification
204
533 Other MetaHeuristic Based Procedures for RCPSP
208
Exact Procedures
213
61 Components of Branch and Bound Procedures
214
611 Branching Schemes
215
612 Search Strategies
216
613 Bounding Rules
218
614 Reduction Rules
219
615 Dominance Rules
220
62 The Branch and Bound Procedure PROGRESS
221
621 The Branching Scheme
222
622 Local Lower Bound Method
224
623 Bounding Rules
226
624 Reduction and Dominance Rules
228
6242 Active Schedule Rules
229
6243 Supersession Rule
231
6244 Schedule storing rules
232
625 Example
236
63 Scattered Branch and Bound
240
631 Principles of Scattered Branch and Bound
241
6312 Subdividing the Solution Space into Regions
243
6313 Swapping Regions
245
Scattered Branch and Bound for GRCPSP
247
6322 Decomposing the Solution Space
248
6323 Swapping Regions
249
6324 Example
251
64 Existing Procedures
252
641 Parallel Branching Scheme
253
642 Serial Branching Scheme
254
643 Delaying Alternatives
256
644 Schedule Schemes
258
Computational Experiments
261
71 Hardware and Software Environment
262
72 Complexity Measures and Data Sets
263
722 Data Sets for RCPSP
267
723 Data Sets for GRCPSP
269
73 Lower Bound Arguments
274
731 Simple Bound Arguments
275
732 Destructive Improvement
278
733 Influence of the Problem Structure
281
734 Comparison with Complex Bound Arguments
284
74 Heuristic Procedures
286
7411 Combinations of Scheduling Schemes and Priority Rules
287
7412 Influence of the Problem Structure
290
7413 MultiPass Performance
293
7414 Comparison to Proprietary Heuristics of Standard Software
295
7475 Results for GRCPSP
296
742 The Tabu Search Procedure RETAPS
300
7421 Analysis of GRCPSP Performance
301
7422 Comparing RETAPS to MultiPass Heuristics
304
7423 Comparing RETAPS to Other Heuristic Procedures for RCPSP
305
75 Exact Procedures
306
7511 Comparing Progress to GDH
307
7512 Analyzing the Efficiency of PROGRESS
309
752 Scattered Branch and Bound
313
7522 Comparing SCATTER to Existing RCPSP Procedures
318
7523 Comparing SCATTER to RETAPS
321
Summary and Conclusions
325
References
333
Index
365
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About the author (2000)

Robert M. Klein, PhD is a Professor in the Department of Anatomy and Cell Biology at the University of Kansas School of Medicine (Kansas City, KS). He teaches the histology course.

George C. Enders, PhD is Associate Professor in the Department of Anatomy and Cell Biology at the University of Kansas School of Medicine (Kansas City, KS). He teaches the anatomy course.