Genetic Algorithms and Fuzzy Multiobjective Optimization
Springer-Verlag New York Inc.
978-1-4613-5594-6 (ISBN)
The intended readers of this book are senior undergraduate students, graduate students, researchers, and practitioners in the fields of operations research, computer science, industrial engineering, management science, systems engineering, and other engineering disciplines that deal with the subjects of multiobjective programming for discrete or other hard optimization problems under fuzziness. Real world research applications are used throughout the book to illustrate the presentation. These applications are drawn from complex problems. Examples include flexible scheduling in a machine center, operation planning of district heating and cooling plants, and coal purchase planning in an actual electric power plant.
1. Introduction.- 1.1 Introduction and historical remarks.- 1.2 Organization of the book.- 2. Foundations of Genetic Algorithms.- 2.1 Outline of genetic algorithms.- 2.2 Coding, fitness, and genetic operators.- 3. Genetic Algorithms for 0–1 Programming.- 3.1 Introduction.- 3.2 Multidimensional 0–1 knapsack problems.- 3.3 0–1 programming.- 3.4 Conclusion.- 4. Fuzzy Multiobjective 0–1 Programming.- 4.1 Introduction.- 4.2 Fuzzy multiobjective 0–1 programming.- 4.3 Fuzzy multiobjective 0–1 programming with fuzzy numbers.- 4.4 Conclusion.- 5. Genetic Algorithms for Integer Programming.- 5.1 Introduction.- 5.2 Multidimensional integer knapsack problems.- 5.3 Integer programming.- 5.4 Conclusion.- 6. Fuzzy Multiobjective Integer Programming.- 6.1 Introduction.- 6.2 Fuzzy multiobjective integer programming.- 6.3 Fuzzy multiobjective integer programming with fuzzy numbers.- 6.4 Conclusion.- 7. Genetic Algorithms for Nonlinear Programming.- 7.1 Introduction.- 7.2 Floating-point genetic algorithms.- 7.3 GENOCOP III.- 7.4 Revised GENOCOP III.- 7.5 Conclusion.- 8. Fuzzy Multiobjective Nonlinear Programming.- 8.1 Introduction.- 8.2 Multiobjective nonlinear programming.- 8.3 Multiobjective nonlinear programming problem with fuzzy numbers.- 8.4 Conclusion.- 9. Genetic Algorithms for Job-Shop Scheduling.- 9.1 Introduction.- 9.2 Job-shop scheduling.- 9.3 Genetic algorithms for job-shop scheduling.- 10.Fuzzy Multiobjective Job-Shop Scheduling.- 10.1 Introduction.- 10.2 Job-shop scheduling with fuzzy processing time and fuzzy due date.- 10.3 Multiobjective job-shop scheduling under fuzziness.- 11.Some Applications.- 11.1 Flexible scheduling in a machining center.- 11.2 Operation planning of district heating and cooling plants.- 11.3 Coal purchase planning in electric powerplants.- References.
Reihe/Serie | Operations Research /Computer Science Interfaces Series ; 14 |
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Zusatzinfo | X, 288 p. |
Verlagsort | New York, NY |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Mathematik / Informatik ► Mathematik ► Allgemeines / Lexika |
Mathematik / Informatik ► Mathematik ► Analysis | |
Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik | |
Wirtschaft ► Betriebswirtschaft / Management | |
ISBN-10 | 1-4613-5594-X / 146135594X |
ISBN-13 | 978-1-4613-5594-6 / 9781461355946 |
Zustand | Neuware |
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