Notice: Undefined index: linkPowrot in C:\wwwroot\wwwroot\publikacje\publikacje.php on line 1275
Publikacje
Pomoc (F2)
[26570] Rozdział:

Design of Real-Time Computer-Based Systems Using Developmental Genetic Programming

w książce:   Handbook of Genetic Programming Applications
ISBN:  978-3-319-20882-4
Wydawca:  Springer International Publishing
Opublikowano: 2015
Liczba stron:  24
Liczba arkuszy wydawniczych:  1.20
 
  Autorzy / Redaktorzy / Twórcy
Imię i nazwisko Wydział Katedra Procent
udziału
Liczba
punktów
Roman Stanisław Deniziak orcid logoWEAiIKatedra Systemów Informatycznych *331.67  
Leszek Ciopiński orcid logoWEAiIKatedra Systemów Informatycznych *331.67  
Grzegorz Pawiński orcid logoWEAiIKatedra Systemów Informatycznych *331.67  

Grupa MNiSW:  Autorstwo rozdziału w monografii naukowej w językach: angielskim, niemieckim, francuskim, hiszpańskim, rosyjskim lub włoskim
Punkty MNiSW: 5


Pełny tekstPełny tekst     DOI LogoDOI    


Abstract:

This chapter presents applications of the developmental genetic programming (DGP) to design and optimize real-time computer-based systems. We show that the DGP approach may be efficiently used to solve the following problems: scheduling of real-time tasks in multiprocessor systems, hardware/software codesign of distributed embedded systems, budget-aware real-time cloud computing. The goal of optimization is to minimize the cost of the system, while all real-time constraints will be satisfied. Since the finding of the best solution is very complex, only efficient heuristics may be applied for real-life systems. Unlike the other genetic approaches where chromosomes represent solutions, in the DGP chromosomes represent system construction procedures. Thus, not the system architecture, but the synthesis process evolves. Finally, a tree describing the construction of a (sub-)optimal solution is obtained and the genotype-to-phenotype mapping is applied to create the target system. Some other ideas concerning other applications of the DGP for optimization of computer-based systems also are outlined.



B   I   B   L   I   O   G   R   A   F   I   A
Alcaraz J, Maroto C (2001) A robust genetic algorithm for resource allocation in project scheduling. Annals of Operations Research, 102, pp. 83-109,
Bąk S, Czarnecki R, Deniziak S (2013) Synthesis of real-time applications for internet of things. In: Pervasive Computing and the Networked World. Lecture Notes in Computer Sci-ence, Springer Berlin Heidelberg, p. 35-49.
Blazewicz J, Lenstra JK, Rinnooy Kan (1983) Scheduling subject to resource constraints: Clas-sification and complexity, Discrete Applied Mathematics, No.5, pp.11–24.
Bouleimen K, Lecocq H (1998). A new efficient simulated annealing algorithm for the re-source-constrained project scheduling problem, Technical Report, Service de Robotique et Automatisation, Universite de Liege.
Brucker P, Knust S, Schoo A, Thiele O (1998) A branch-and-bound algorithm for the re-source-constrained project scheduling problem. European Journal of Operational Research, 107: 272–288.
Buyya R, Broberg J, Goscinski A (2011) Cloud Computing: Principles and Paradigms. Wiley Press, New York, USA
Deiranlou M, Jolai F (2009) A New Efficient Genetic Algorithm for Project Scheduling under Resource Constrains. World Applied Sciences Journal, 7 (8): pp. 987-997,
Demeulemeester EL, Herroelen WS (1997) New benchmark results for the resource-constrained project scheduling problem. Management Science, 43: 1485–1492
Demeulemeester EL, Herroelen WS (2002) Project Scheduling. A Research Handbook, Spring-er
Deniziak S, Sapiecha, K (1998). An efficient algorithm of perfect state encoding for CPLD based systems.
Deniziak S (2004) Cost-efficient synthesis of multiprocessor heterogeneous systems. Control and Cybernetics 33(2):341–355
Deniziak S, Górski A (2008) Hardware/Software Co-Synthesis of Distributed Embedded Sys-tems Using Genetic Programming. Lecture Notes in Computer Science, Springer-Verlag, pp. 83-93.
Deniziak S, Wieczorek S (2012a) Parallel Approach to the Functional Decomposition of Logi-cal Functions Using Developmental Genetic Programming. Lecture Notes in Computer Sci-ence 7203:406-415.
Deniziak S, Wieczorek S (2012b) Evolutionary Optimization of Decomposition Strategies for Logical Functions. Lecture Notes in Computer Science 7269, pp. 182-189
Deniziak S, Ciopiński L, Pawiński G et al (2014) Cost Optimization of Real-Time Cloud Ap-plications Using Developmental Genetic Programming, IEEE/ACM 7th International Con-ference on Utility and Cloud Computing
Dick RP, Jha NK (1998) MOGAC: A Multiobjective Genetic Algorithm for the Co-Synthesis of Hardware-Software Embedded Systems. IEEE Trans. on Computer Aided Design of Inte-grated Circuits and Systems 17(10):920–935
Drexl A, Kimms A (2001) Optimization guided lower and upper bounds for the resource in-vestment problem, Journal of the Operational Research Society 52 pp.340–351
Dorndorf U, Pesch E and Toàn Phan-Huy (2000) Constraint propagation techniques for the disjunctive scheduling problem. Artificial intelligence 122.1 (2000): 189-240.
Dorigo M, Stützle T (2004) Ant Colony Optimization. Massachusets Institute of Technology, USA
Frankola T, Golub M and Jakobovic D (2008) Evolutionary algorithms for the resource con-strained scheduling problem. In Proceedings of 30th International Conference on Infor-mation Technology Interfaces 7269:715-722
Hartmann S (1998) A Competitive Genetic Algorithm for Resource-Constrained Project Scheduling. Naval Research Logistics, 45:733-750
Hartmann S, Briskorn D (2010) A survey of variants and extensions of the resource-constrained project scheduling problem. European journal of operational research : EJOR. - Amsterdam : Elsevier 207, 1 (16.11.), pp. 1-15
Hendrickson C, Tung A (2008) Advanced Scheduling Techniques. In: Project Management for Construction, cmu.edu (2.2 ed.), Prentice Hall
Keller R, Banzhaf W (1999) The Evolution of Genetic Code in Genetic Programming. In: Proc. of the Genetic and Evolutionary Computation Conference, pp. 1077–1082
Klein R, (2000) Scheduling of Resource-Constrained Projects,.Springer Science & Business Media
Kolish R, Sprecher A (1996). Psplib - a project scheduling library. European journal of opera-tional research, 96:205-216.
Kolisch R, Hartmann S (1999) Heuristic algorithms for the resource-constrained project scheduling problem: Classification and computational analysis. Springer US
Kolisch R, Hartmann S (2006) Experimental investigation of heuristics for resource-constrained project scheduling: An update. European journal of operational research, 174:23-37
Koza JR (1992) Genetic Programming: On the Programming of Computers by Means of Natu-ral Selection, MIT Press, Cambridge, MA, USA
Koza J, Keane MA, Streeter MJ et al. (2003) Genetic Programming IV: Routine Human-Competitive Machine Intelligence. Kluwer Academic Publisher, Norwell
Koza JR (2010) Human-competitive results produced by genetic programming. In Genetic Programming and Evolvable Machines, pp.251-284
Nubel H (2001) The resource renting problem subject to temporal constraints. OR Spektrum 23: 359–381
Pawiński G. Sapiecha K (2012) Resource allocation optimization in Critical Chain Method. Annales Universitatis Mariae Curie-Sklodowska sectio Informaticales, 12 (1), p 17–29
Pawiński G, Sapiecha K (2014) Cost-efficient project management based on critical chain method with partial availability of resources. CONTROL AND CYBERNETICS, 43(1)
Pawiński G, Sapiecha K (2014) A Developmental Genetic Approach to the cost/time trade-off in Resource Constrained Project Scheduling. IEEE Federated Conference on Computer Sci-ence and Information Systems
Pinedo M, Chao X (1999) Operations Scheduling with applications in Manufacturing. Ir-win/McGraw-Hill, Boston, New York, NY, USA, 2nd edition.
Sapiecha K, Ciopiński L, Deniziak S (2014) An Application of Developmental Genetic Pro-gramming for Automatic Creation of Supervisors of Multitask Real-Time Object-Oriented Systems. IEEE Federated Conference on Computer Science and Information Systems, 2014.
Tomassini M (1999) Parallel and distributed evolutionary algorithms: A review. In P. Neittaanmki K. Miettinen, M. Mkel and J. Periaux, editors, Evolutionary Algorithms in En-gineering and Computer Science, J. Wiley and Sons, Chichester
Watson JD, Hopkins NH, Roberts JW et al. (1992). Molecular Biology of the Gene. Benjamin Cummings. Menlo Park, CA.
Węglarz J et al. (2011) Project scheduling with finite or infinite number of activity processing modes–A survey. European Journal of Operational Research 208.3: 177-205.
Yen, TY, Wolf WH (1995) Sensivity-Driven Co-Synthesis of Distributed Embedded Systems. In: Proc. of the Int. Symposium on System Synthesis, pp. 4–9
Yen, TY, Wolf WH (1997) Yen, T.-Y., Wolf, W.: Hardware-Software Co-synthesis of Distrib-uted Embedded Systems. Springer, Heidelberg