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Ways and Means of Applying Genetic Algorithms for Job Shop Scheduling


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1 Computer Science Department, IMS Engineering College, Ghaziabad, U.P, India
     

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This paper presents a study of various genetic algorithms developed for solving the Job shop scheduling problem. Various approaches such as crossover operators, mutations and constrained problem statement have been applied to obtain optimal solutions. Some of the key areas studied are: , penalty function, VND[Variable Neighborhood Descent Algorithm], random keys, JOX[ job based order crossover], GOX[generalized order crossover] and OBGT[order-based Giffler and Thompson].

Keywords

Job Shop Scheduling, Genetic Algorithm
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  • Liang Sun , Xiaochun Cheng, Yanchun Liang,” Solving Job Shop Scheduling Problem Using Genetic Algorithm with Penalty Function” International Journal of Intelligent Information Processing Volume 1, Number 2, December 2010
  • Christian Bierwirth in his paper “A Generalized Permutation Approach to Job Shop Scheduling Problem with Genetic Algorithms”
  • Isao Ono Masayuki Yamamura Shigenobu Kobayashi in their paper, “A Genetic Algorithm for Job-shop Scheduling Problems Using Job-based Order Crossover” Proc. of ICEC'96, pp.547-552 (1996)
  • José Fernando Gonçalves, Jorge José de Magalhães Mendes, Maurício G.C. Resende in their paper “A Hybrid Genetic Algorithm for the Job Shop Scheduling Problem”
  • Jie Gao, Linyan Sun, Mitsuo Gen in their paper, “A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems” Computers & Operations Research 35 (2008) 2892 --- 2907
  • Manuel Vazquez in his paper,” A comparison of genetic algorithms for job shop scheduling” conventional genetic algorithm for job shop scheduling by ryohei nakano and takeshi yamada
  • P. Brucker, B. Jurisch, B. Sievers, “A branch and bound algorithm for job shop scheduling problem”, Discrete Applied Math, vol. 49, pp. 105-127, 1994.
  • T. Lorigeon, “A dynamic programming algorithm for scheduling jobs in a twomachine open shop with an availability constraint”, Journal of the Operational Research Society, vol. 53, no. 11, pp. 1239-1246, 2002.
  • J. Gao, M. Gen, L. Y. Sun, “A hybrid of genetic algorithm and bottleneck shifting for multiobjective flexible job shop scheduling problems”, Computers and Industrial Engineering, vol. 53, no. 1, pp. 149-162, 2007.
  • C. Y. Zhang, P. G. Li, Y. Q. Rao, “A very fast TS/SA algorithm for the job shop scheduling problem”, Computers & Operations Research, vol. 35, pp. 282-294, 2008.
  • J. H. Holland, Adaptation in Natural and Artificial Systems. Ann Arbor, MI: University of Michigan Press, 1975.

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  • Ways and Means of Applying Genetic Algorithms for Job Shop Scheduling

Abstract Views: 356  |  PDF Views: 0

Authors

Shruti Kapoor
Computer Science Department, IMS Engineering College, Ghaziabad, U.P, India
Swati Singh
Computer Science Department, IMS Engineering College, Ghaziabad, U.P, India
Shelly Chikara
Computer Science Department, IMS Engineering College, Ghaziabad, U.P, India
Shivangi Garg
Computer Science Department, IMS Engineering College, Ghaziabad, U.P, India
Vijai Singh
Computer Science Department, IMS Engineering College, Ghaziabad, U.P, India

Abstract


This paper presents a study of various genetic algorithms developed for solving the Job shop scheduling problem. Various approaches such as crossover operators, mutations and constrained problem statement have been applied to obtain optimal solutions. Some of the key areas studied are: , penalty function, VND[Variable Neighborhood Descent Algorithm], random keys, JOX[ job based order crossover], GOX[generalized order crossover] and OBGT[order-based Giffler and Thompson].

Keywords


Job Shop Scheduling, Genetic Algorithm

References