ABSTRACT
The job-shop scheduling problem is a NP-hard combinational optimization and one of the best-known machine scheduling problems. Genetic algorithm is an effective search algorithm to solve this problem; however the quality of the best solution obtained by the algorithm has to improve due to its limitation. The paper proposes a novel hybrid optimization algorithm for the job-shop scheduling problem, which applies chaos theory on the basis of combining genetic programming and genetic algorithm. It improves the quality of the initial population by using chaos optimization method; it maintains the population diversity by chaotic disturbance and anti-equilibration in crossover of genetic programming. Three traversals are adopted to reduce the chance of reaching local optimal solution. Moreover, a scheme of changing weight is proposed during the process of evolution to increase the global exploration capability. The experimental results show that the effectiveness and good quality of the hybrid algorithm is obvious from some benchmarks.
- Lageweg B. J., Lenstra J. K., Rinnooy Kan A. H. G. Job-shop scheduling by implicit enumeration. Management Science, 1977, 24:441--450.Google ScholarDigital Library
- Adams J., E. Balas, D. Zawack. The shifting bottleneck procedure for job shop scheduling. Management Science, 1988, 34:391--401. Google ScholarDigital Library
- Van Laarhoven P. J. M., Aarts E. H. L., Leenstra J. K. Job shop scheduling by simulated annealing. Operations Research, 1992, 40: 113--125. Google ScholarDigital Library
- Dell'Amico M, Trubian M. Applying tabu search to the job shop scheduling problem. Annals of Operations Research, 1993, 40:231--252. Google ScholarDigital Library
- T.Yamada, R. Nakano. A genetic algorithm applicable to large-scale job-shop problems. In 2nd PPSN, Proceedings of the 2nd International Workshop on Parallel Problem Solving from Nature, 1992: 281--290.Google Scholar
- D.Crafti. 2004 A Job Shop Scheduler using a Genetic Tree Algorithm: in School of Computer Science and Software Engineering. Doctoral Thesis. Melbourne, Australia: Manash University, Clayton Campus, 2004: 63.Google Scholar
- Tel Tamas, Gruiz Marton. Chaotic dynamics: An introduction based on classical mechanics. Cambridge University Press, 2006.Google Scholar
- Li, T. Y. and Yorke, J. A. Period three implies chaos. Am. Math. Monthly, 1975: 985--992.Google Scholar
- Feigenbaum, M.J. Quantitive universality for a class of nonlinear transformations. J. Stat. Phys. 1978, 19: 25--52.Google ScholarCross Ref
- Poli R., Langdon W. B., McPhee N. F. A Field Guide to Genetic Programming, freely available via Lulu.com, 2008. Google ScholarDigital Library
- Marco Tomassini, L. Luthi, M. Giacobini and W. B. Langdon. The Structure of the Genetic Programming Collaboration Network. Genetic Programming and Evolvable Machines, 2007, 8(1): 97--103. Google ScholarDigital Library
- Koza, J. R., et al: Genetic Programming III: Darwinian Invention and Problem Solving. Morgan Kaufmann, San Francisco, 1999. Google ScholarDigital Library
- Koza, J. R., Keane, M.A., Streeter, M.J., Mydlowec, W., Yu, J., and Lanza, G. Genetic Programming IV: Routine Human-Competitive Machine Intelligence, Springer, 2003. Google ScholarDigital Library
- Adams J., Balas E., and Zawack D. The shifting bottleneck procedure for job shop scheduling. Management Scince, 1988, 34(3): 391--401. Google ScholarDigital Library
- Martyn M. T., Zatloukal P.D., Source M. Visualization and Analysis of Interfacial Instability in Coextrusion of LDPE Melt. Plastics, Rubber and Composites, 2004, 33 (1): 27--35.Google ScholarCross Ref
- Vaddiraju S. R., Kostic M., Reifscheider I., et al. Extrusion Simulation and Experimental Validation to Optimize Precision Die Design. ANTEC, 2004, 1:76--80.Google Scholar
- Matsunaga K., Kajiwera T., Funatsu K. Numerical Simulation of Multi-layer Flow for Polymer Melts- a Study of the Effect of Viscoelasticity on Interface Shape of Polymers within Dies. Polymer Engineering and Science, 1998, 38(7): 1099--1111.Google ScholarCross Ref
- Rincon A. J., Hrymak A. N., Vlachopoulos J. Transient Finite Element Analysis of Generalized Newtonian Coextrusion Flows in Complex Geometries. International Journal for Numerical Methods in Fluids, 1998, 28(8): 1159--1181.Google ScholarCross Ref
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- A hybrid optimization algorithm for the job-shop scheduling problem
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