Scheduling of production processes:
Saved in:
| Format: | Book |
|---|---|
| Language: | English |
| Published: |
New York [u.a.]
Ellis Horwood
1993
|
| Edition: | 1. publ. |
| Series: | Ellis Horwood series in artificial intelligence : Foundations and concepts
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XII, 181 S. graph. Darst. |
| ISBN: | 0130751367 |
Staff View
MARC
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| 245 | 1 | 0 | |a Scheduling of production processes |c eds.: Jürgen Dorn ... |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a New York [u.a.] |b Ellis Horwood |c 1993 | |
| 300 | |a XII, 181 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Ellis Horwood series in artificial intelligence : Foundations and concepts | |
| 650 | 4 | |a Production scheduling | |
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Record in the Search Index
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| adam_text | Table of Contents
1 Two Paradigms of Combinatorial Production Scheduling 1
Introduction 1
An Outline of Scheduling Methodology 4
Comparison of Paradigms 12
This B ook s Contribution 15
References 17
2 Scheduling as a Constraint Satisfaction Problem: Theory and Practice 22
Introduction 22
A Simple Scheduling Problem 23
The (Binary) Constraint Satisfaction Problem 23
Representing the Scheduling Problem as CSP 24
Forward Checking and the Scheduling Problem 27
Conclusion 28
References 29
3 Scheduling and Uncertainty Reasoning 31
Introduction 31
Uncertainty in AI 32
The Scheduling Problem 34
The Probabilistic Argument 34
An Example 35
Summary 46
References 46
4 A Case based Approach to Scheduling Constraints 48
Introduction 48
Toy Car Production at the IUCCIM 50
The Case Based Scheduler CBS 1 50
Cases 53
Retrieval 56
Adaptation 58
Discussion ^
Conclusions 6*
References 60
viii Table of Contents
5 Enhancing Genetic Search to Schedule a Production Unit 61
Introduction 61
The Scheduling Problem 62
Genetic Scheduler Design 64
Experimental Evaluation 67
Conclusion 68
References 68
6 Distributed Genetic Algorithms for Resource Allocation 70
Introduction 70
Genetic Algorithms 71
A Simple Prototype 72
Distributed GAs for Resource Allocation 73
Extensions 74
Conclusion 75
References 75
Appendix 76
7 A Multi agent Model for the Resource Allocation Problem: a Reactive
Approach 79
Context and Motivations 79
The Multi agent Model 80
Reactivity 81
Conclusion and Perspectives 84
References 85
8 A Method for Flow shop Scheduling Problems with Due Dates 86
Introduction 86
The Problem 87
References 93
9 Using a Local Improvement Algorithm to Solve a Constraint Satisfaction
Problem in Rostering 94
The Rostering Problem 94
Compiling the Rota 95
A Mathematical Programming Approach 95
Constraint Satisfaction Problems 96
The Rota Compilation Problem as a CSP 97
Improving a Feasible Solution 99
Results and Conclusions 101
References 102
Table of Contents ix
10 Advanced Job shop Scheduling in Aeronautical Manufacturing 103
The Scheduling Context 103
The OPAL System 104
Extensions and Generalization 110
Synthesis and Conclusion 111
References 112
11 The Temporal Model of CRONOS III: A Knowledge based System for
Production Scheduling 113
Introduction 113
CRONOS III 114
TEMS: Basic Concepts 119
TEMS: Soft Temporal Constraints 123
Temporal Reasoning 125
Conclusions 127
References !28
12 INTESIMPRO Simple Dynamic Scheduling for Discrete Manufacturing 130
Introduction 30
Model of the Problem 1 31
Representation 131
Incremental Solution 132
Backtracking 133
Relaxation I35
Dynamic Behaviour 136
Conclusion J0
References 30
13 Scheduling and Routing Heuristics in an Automated Job shop Environment 139
Introduction ^
Literature Review
A Hierarchical Concept of Routing and Scheduling 142
Numerical Evaluation
References
14 Meta Scheduling Using Dynamic Scheduling Knowledge 151
Scheduling j5*
Dynamic Scheduling Knowledge
Representation of Scheduling Knowledge by Heuristics 156
META_PLAN: Using Dynamic Planning Knowledge 159
Conclusion j^
References
x Table of Contents
15 Task oriented Design for Scheduling Applications 163
Introduction 163
Two Scheduling Applications in Steelmaking 166
The Models of Expertise 168
Reuse of the Task Model 175
Conclusions 176
References 177
Index 179
Tables of Figures, Tables and Algorithms
Figure 3 1: The sample problem (temporal relation constraints) 36
Figure 3 2: Global utility functions for the sample problem 38
Figure 3 3: Example STP distribution for operations in Pa 39
Figure 3 4: Example STP distribution for operations in Pb 40
Figure 3 5: Example STP distribution for operations in Pc 41
Figure 3 6: From STP distribution to IPD density 41
Figure 3 7: PCPS for the sample problem 42
Figure 3 8: The PCP construction process (Berry, 1991) 43
Figure 3 9: Dissection of the PCP for R2 44
Figure 4 1: The structure of CBS 1 52
Figure 6 1: A simple genetic algorithm 71
Figure 6 2: Object representation of a genetic agent 76
Figure 6 3: Object representation of a chromosome 77
Figure 6 4: Current domains and durations of the operations 78
Figure 6 5: Optimal solution found by the genetic algorithm 78
Figure 7 1: Change of optimal solutions j*2
Figure 7 2: Difference new solution / previous solution 83
Figure 7 3: Refusal and ejections ^4
Figure 8 1: Architecture for job sequencing â„¢
Figure 8 2: Decision tree for 7 job example ^
Figure 10 1: The fuzzy sets membership functions 1 °6
Figure 11 1: CRONOS m architecture J J ^
Figure 11 2: Performance of CRONOS m 119
Figure 11 3: The start / finish plane j^O
Figure 11 4: A sopo in the start / finish plane j^
Figure 11 5: Examples of weight functions j 24
Figure 11 6 An example of temporal constraint propagation l x
Figure 12 1: Representation of the relationship between activity and operation 32
Figure 12 2: Semantic Network for the activity concept j 32
Figure 14 1: AND / OR tree: problem space of scheduling »52
Figure 14 2: Order based planning skeleton with possible rules j 54
Figure 14 3: Planning skeletons for scheduling ^
Figure 14 4: Possible rules usable for selection in skeletons ^
Figure 14 5: Heuristic ~
Figure 14 6: Then part of heuristic
Figure 14 7: Two examples of heuristics represented with hera » _«
Figure 14 8: System architecture of META_PLAN ^
Figure 14 9: Interpretation rules „
Figure 15 1: Models of expertise Q
Figure 15 2: Generic domain theory ^ 7Q
Figure 15 3: Temporal description of process plan ^
Figure 15 4: Process plan
xii Tables of Figures, Tables and Algorithms
Table 3 1: The sample problem (resource requirement constraints) 37
Table 4 1: Sample order 54
Table 4 2: Internal constraints 54
Table 4 3: Schedule for a sample machine 54
Table 4 4: A conflict situation 55
Table 4 5: A new order and current machine status 57
Table 5 1: Overview of the production unit 63
Table 5 2: Results of schedule optimization 67
Table 6 1: Operations of job set 72
Table 6 2: Optimal solution 73
Table 8 1: A simple flow shop example of seven jobs and three workstations 89
Table 8 2: Test runs 92
Table 9 1: Swaps within a session 100
Table 13 1: Resource matrix 142
Table 13 2: Selected batch of variations 148
Table 13 3: Description of selected variations 148
Table 13 4: Relation SPT to best TABU 148
Algorithm 11 1: S cheduling strategy 118
Algorithm 12 1: Exchanging operations 135
Algorithm 12 2: Resource breakdown rescheduling 137
Algorithm 13 1: Routing 144
Algorithm 13 2: Exchange mechanism 146
Algorithm 15 1: search best slot inference 172
Algorithm 15 2: schedule job task 173
Algorithm 15 3: schedule resource task 173
Algorithm 15 4: mixed job / resource based strategy 174
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| discipline | Wirtschaftswissenschaften |
| edition | 1. publ. |
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| illustrated | Illustrated |
| indexdate | 2024-07-09T17:32:57Z |
| institution | BVB |
| isbn | 0130751367 |
| language | English |
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| physical | XII, 181 S. graph. Darst. |
| publishDate | 1993 |
| publishDateSearch | 1993 |
| publishDateSort | 1993 |
| publisher | Ellis Horwood |
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| series2 | Ellis Horwood series in artificial intelligence : Foundations and concepts |
| spelling | Scheduling of production processes eds.: Jürgen Dorn ... 1. publ. New York [u.a.] Ellis Horwood 1993 XII, 181 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Ellis Horwood series in artificial intelligence : Foundations and concepts Production scheduling Scheduling (DE-588)4179449-7 gnd rswk-swf Produktionsplanung (DE-588)4047360-0 gnd rswk-swf Produktionsprozess (DE-588)4123984-2 gnd rswk-swf Scheduling (DE-588)4179449-7 s Produktionsprozess (DE-588)4123984-2 s DE-604 Produktionsplanung (DE-588)4047360-0 s Dorn, Jürgen Sonstige oth HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=006112791&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Scheduling of production processes Production scheduling Scheduling (DE-588)4179449-7 gnd Produktionsplanung (DE-588)4047360-0 gnd Produktionsprozess (DE-588)4123984-2 gnd |
| subject_GND | (DE-588)4179449-7 (DE-588)4047360-0 (DE-588)4123984-2 |
| title | Scheduling of production processes |
| title_auth | Scheduling of production processes |
| title_exact_search | Scheduling of production processes |
| title_full | Scheduling of production processes eds.: Jürgen Dorn ... |
| title_fullStr | Scheduling of production processes eds.: Jürgen Dorn ... |
| title_full_unstemmed | Scheduling of production processes eds.: Jürgen Dorn ... |
| title_short | Scheduling of production processes |
| title_sort | scheduling of production processes |
| topic | Production scheduling Scheduling (DE-588)4179449-7 gnd Produktionsplanung (DE-588)4047360-0 gnd Produktionsprozess (DE-588)4123984-2 gnd |
| topic_facet | Production scheduling Scheduling Produktionsplanung Produktionsprozess |
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