Constraint-Based Scheduling Applying Constraint Programming to Scheduling Problems

Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the...

Full description

Bibliographic Details
Main Authors: Baptiste, Philippe, Le Pape, Claude (Author), Nuijten, Wim (Author)
Format: eBook
Language:English
Published: New York, NY Springer US 2001, 2001
Edition:1st ed. 2001
Series:International Series in Operations Research & Management Science
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
LEADER 04155nmm a2200373 u 4500
001 EB000624139
003 EBX01000000000000000477221
005 00000000000000.0
007 cr|||||||||||||||||||||
008 140122 ||| eng
020 |a 9781461514794 
100 1 |a Baptiste, Philippe 
245 0 0 |a Constraint-Based Scheduling  |h Elektronische Ressource  |b Applying Constraint Programming to Scheduling Problems  |c by Philippe Baptiste, Claude Le Pape, Wim Nuijten 
250 |a 1st ed. 2001 
260 |a New York, NY  |b Springer US  |c 2001, 2001 
300 |a XIII, 198 p  |b online resource 
505 0 |a 1. Introduction -- 1.1 Introduction to Constraint Programming -- 1.2 Scheduling Theory -- 1.3 A Constraint-Based Scheduling Model -- 2. Propagation of the One-Machine Resource Constraint -- 2.1 Non-Preemptive Problems -- 2.2 Preemptive Problems -- 3. Propagation of Cumulative Constraints -- 3.1 Fully Elastic Problems -- 3.2 Preemptive Problems -- 3.3 Non-Preemptive Problems -- 4. Comparison of Propagation Techniques -- 4.1 Constraint Propagation Rules -- 4.2 Dominance Relations -- 4.3 Non-Dominance Relations -- 4.4 Summary -- 5. Propagation of Objective Functions -- 5.1 Total Weighted Number of Late Activities -- 5.2 Sum of Transition Times and Sum of Transition Costs -- 5.3 Conclusion -- 6. Resolution of Disjunctive Problems -- 6.1 Job-Shop Scheduling -- 6.2 Open-Shop Scheduling -- 6.3 Preemptive Job-Shop Scheduling -- 7. Cumulative Scheduling Problems -- 7.1 General Framework -- 7.2 Hybrid Flow-Shop Scheduling -- 7.3 Resource-Constrained Project Scheduling -- 7.4 Conclusion -- 8. Min-Sum Scheduling Problems -- 8.1 Minimizing the Weighted Number of Late Jobs -- 8.2 Minimizing Makespan and Sum of Transition Times -- 9. Conclusion -- 10. Summary of Notation -- References 
653 |a Operations research 
653 |a Optimization 
653 |a Computer science 
653 |a Calculus of Variations and Optimization 
653 |a Theory of Computation 
653 |a Mathematical optimization 
653 |a Operations Research and Decision Theory 
653 |a Calculus of variations 
700 1 |a Le Pape, Claude  |e [author] 
700 1 |a Nuijten, Wim  |e [author] 
041 0 7 |a eng  |2 ISO 639-2 
989 |b SBA  |a Springer Book Archives -2004 
490 0 |a International Series in Operations Research & Management Science 
028 5 0 |a 10.1007/978-1-4615-1479-4 
856 4 0 |u https://doi.org/10.1007/978-1-4615-1479-4?nosfx=y  |x Verlag  |3 Volltext 
082 0 |a 519.6 
520 |a Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsible for the "hardness" of the scheduling problem. Chapters 6, 7, and 8 are dedicated to the resolution of several scheduling problems. These examples illustrate the use and the practical efficiency of the constraint propagation methods of the previous chapters. They also show that besides constraint propagation, the exploration of the search space must be carefully designed, taking into account specific properties of the considered problem (e.g., dominance relations, symmetries, possible use of decomposition rules). Chapter 9 mentions various extensions of the model and presents promising research directions