Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 367152, 11 pages
http://dx.doi.org/10.1155/2014/367152
Research Article
Diversity Controlling Genetic Algorithm for Order Acceptance and Scheduling Problem
College of Information System and Management, National University of Defense Technology, Changsha 410073, China
Received 2 November 2013; Accepted 9 January 2014; Published 23 February 2014
Academic Editor: Wei-Chiang Hong
Copyright © 2014 Cheng Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Linked References
- S. A. Slotnick, “Order acceptance and scheduling: a taxonomy and review,” European Journal of Operational Research, vol. 212, no. 1, pp. 1–11, 2011. View at Publisher · View at Google Scholar · View at Scopus
- N. G. Hall and M. J. Magazine, “Maximizing the value of a space mission,” European Journal of Operational Research, vol. 78, no. 2, pp. 224–241, 1994. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- V. S. Gordon and V. A. Strusevich, “Single machine scheduling and due date assignment with positionally dependent processing times,” European Journal of Operational Research, vol. 198, no. 1, pp. 57–62, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- K. Charnsirisakskul, P. M. Griffin, and P. Keskinocak, “Order selection and scheduling with leadtime flexibility,” IIE Transactions, vol. 36, no. 7, pp. 697–707, 2004. View at Publisher · View at Google Scholar · View at Scopus
- K. Charnsirisakskul, P. M. Griffin, and P. Keskinocak, “Pricing and scheduling decisions with leadtime flexibility,” European Journal of Operational Research, vol. 171, no. 1, pp. 153–169, 2006. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- C. Oǧuz, F. Sibel Salman, and Z. B. Yalçin, “Order acceptance and scheduling decisions in make-to-order systems,” International Journal of Production Economics, vol. 125, no. 1, pp. 200–211, 2010. View at Publisher · View at Google Scholar · View at Scopus
- F. T. Nobibon and R. Leus, “Exact algorithms for a generalization of the order acceptance and scheduling problem in a single-machine environment,” Computers and Operations Research, vol. 38, no. 1, pp. 367–378, 2011. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- S. A. Slotnick and T. E. Morton, “Order acceptance with weighted tardiness,” Computers and Operations Research, vol. 34, no. 10, pp. 3029–3042, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- B. Cesaret, C. Oǧuz, and F. S. Salman, “A tabu search algorithm for order acceptance and scheduling,” Computers and Operations Research, vol. 39, no. 6, pp. 1197–1205, 2012. View at Publisher · View at Google Scholar · View at Scopus
- S.-W. Lin and K.-C. Ying, “Increasing the total net revenue for single machine order acceptance and scheduling problems using an artificial bee colony algorithm’,” Journal of the Operational Research Society, vol. 64, no. 2, pp. 293–311, 2012. View at Publisher · View at Google Scholar
- W. O. Rom and S. A. Slotnick, “Order acceptance using genetic algorithms,” Computers and Operations Research, vol. 36, no. 6, pp. 1758–1767, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- Y.-Y. Xiao, R.-Q. Zhang, Q.-H. Zhao, and I. Kaku, “Permutation flow shop scheduling with order acceptance and weighted tardiness,” Applied Mathematics and Computation, vol. 218, no. 15, pp. 7911–7926, 2012. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- B. Yang and J. Geunes, “A single resource scheduling problem with job-selection flexibility, tardiness costs and controllable processing times,” Computers and Industrial Engineering, vol. 53, no. 3, pp. 420–432, 2007. View at Publisher · View at Google Scholar · View at Scopus
- C. Cheng, Z. Yang, and L. Xing, “An improved genetic algorithm with local search for order acceptance and scheduling problems,” in Proceedings of the IEEE Symposium on Computational Intelligence in Production and Logistics System, Singapore. View at Publisher · View at Google Scholar
- J.-M. Renders and S. P. Flasse, “Hybrid methods using genetic algorithms for global optimization,” IEEE Transactions on Systems, Man, and Cybernetics B, vol. 26, no. 2, pp. 243–258, 1996. View at Publisher · View at Google Scholar · View at Scopus
- P. C. Chu and J. E. Beasley, “A genetic algorithm for the generalised assignment problem,” Computers and Operations Research, vol. 24, no. 1, pp. 17–23, 1997. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- B. Mc Ginley, J. Maher, C. O'Riordan, and F. Morgan, “Maintaining healthy population diversity using adaptive crossover, mutation, and selection,” IEEE Transactions on Evolutionary Computation, vol. 15, no. 5, pp. 692–714, 2011. View at Publisher · View at Google Scholar · View at Scopus
- M. Crepinsek, S. H. Liu, and M. Mernik, “Exploration and exploitation in evolutionary algorithms: a survey,” ACM Computing Surveys, vol. 45, no. 3, article 35, pp. 31–35, 2013. View at Publisher · View at Google Scholar
- T. Vidal, T. G. Crainic, M. Gendreau, and C. Prins, “A hybrid genetic algorithm with adaptive diversity management for a large class of vehicle routing problems with time-windows,” Computers and Operations Research, vol. 40, pp. 475–489, 2013. View at Publisher · View at Google Scholar
- T. Vidal, T. G. Crainic, M. Gendreau, N. Lahrichi, and W. Rei, “A hybrid genetic algorithm for multidepot and periodic vehicle routing problems,” Operations Research, vol. 60, no. 3, pp. 611–624, 2012. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
- L. Masisi, V. Nelwamondo, and T. Marwala, “The use of entropy to measure structural diversity,” in Proceedings of the IEEE 6th International Conference on Computational Cybernetics (ICCC '08), pp. 41–45, November 2008. View at Publisher · View at Google Scholar · View at Scopus
- A. Misevičius, “Generation of grey patterns using an improved genetic-evolutionary algorithm: some new results,” Information Technology and Control, vol. 40, no. 4, pp. 330–343, 2011. View at Google Scholar · View at Scopus
- E. Burke, S. Gustafson, and G. Kendall, “Diversity in genetic programming: an analysis of measures and correlation with fitness,” IEEE Transactions on Evolutionary Computation, vol. 8, no. 1, pp. 47–62, 2004. View at Publisher · View at Google Scholar · View at Scopus
- T. Friedrich, P. S. Oliveto, D. Sudholt, and C. Witt, “Analysis of diversity-preserving mechanisms for global exploration,” Evolutionary Computation, vol. 17, no. 4, pp. 455–476, 2009. View at Publisher · View at Google Scholar · View at Scopus
- J. C. Bean, “Genetic algorithms and random keys for sequencing and optimization,” ORSA Journal on Computing, vol. 6, pp. 154–160, 1994. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
- J. C. Potts, T. D. Giddens, and S. B. Yadav, “Development and evaluation of an improved genetic algorithm based on migration and artificial selection,” IEEE Transactions on Systems, Man and Cybernetics, vol. 24, no. 1, pp. 73–86, 1994. View at Publisher · View at Google Scholar · View at Scopus
- P. W. Poon and J. N. Carter, “Genetic algorithm crossover operators for ordering applications,” Computers and Operations Research, vol. 22, no. 1, pp. 135–147, 1995. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- H.-F. Wang and K.-Y. Wu, “Hybrid genetic algorithm for optimization problems with permutation property,” Computers and Operations Research, vol. 31, no. 14, pp. 2453–2471, 2004. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- T. Murata, H. Ishibuchi, and H. Tanaka, “Genetic algorithms for flowshop scheduling problems,” Computers and Industrial Engineering, vol. 30, no. 4, pp. 1061–1071, 1996. View at Publisher · View at Google Scholar · View at Scopus
- R. Ruiz and T. Stützle, “A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem,” European Journal of Operational Research, vol. 177, no. 3, pp. 2033–2049, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- S. F. Galan and O. J. Mengshoel, “A novel mating approach for genetic algorithm,” Evolutionary Computation, vol. 21, no. 2, pp. 197–229, 2013. View at Publisher · View at Google Scholar