A new hybrid genetic algorithm for job shop scheduling problem

Job shop scheduling problem is a typical NP-hard problem. To solve the job shop scheduling problem more effectively, some genetic operators were designed in this paper. In order to increase the diversity of the population, a mixed selection operator based on the fitness value and the concentration value was given. To make full use of the characteristics of the problem itself, new crossover operator based on the machine and mutation operator based on the critical path were specifically designed. To find the critical path, a new algorithm to find the critical path from schedule was presented. Furthermore, a local search operator was designed, which can improve the local search ability of GA greatly. Based on all these, a hybrid genetic algorithm was proposed and its convergence was proved. The computer simulations were made on a set of benchmark problems and the results demonstrated the effectiveness of the proposed algorithm.

[1]  Yanchun Liang,et al.  An Effective PSO and AIS-Based Hybrid Intelligent Algorithm for Job-Shop Scheduling , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[2]  Mitsuo Gen,et al.  Genetic algorithms and engineering design , 1997 .

[3]  Wang Shu.  Techniques for the Job Shop Scheduling Problem: a Survey , 2003 .

[4]  Ling Wang,et al.  An effective hybrid optimization strategy for job-shop scheduling problems , 2001, Comput. Oper. Res..

[5]  Lawrence Davis,et al.  Job Shop Scheduling with Genetic Algorithms , 1985, ICGA.

[6]  Peigen Li,et al.  A New Hybrid GA/SA Algorithm for the Job Shop Scheduling Problem , 2005, EvoCOP.

[7]  Congxin Li,et al.  Research on immune genetic algorithm for solving the job-shop scheduling problem , 2007 .

[8]  Gu Qingming,et al.  A HYBRID GENETIC ALGORITHM FOR JOB SHOP SCHEDULING PROBLEM , 1998 .

[9]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[10]  Egon Balas,et al.  Machine Sequencing Via Disjunctive Graphs: An Implicit Enumeration Algorithm , 1969, Oper. Res..

[11]  Mauro Dell'Amico,et al.  Applying tabu search to the job-shop scheduling problem , 1993, Ann. Oper. Res..

[12]  Jean-Charles Billaut,et al.  A tabu search and a genetic algorithm for solving a bicriteria general job shop scheduling problem , 2008, Eur. J. Oper. Res..

[13]  Ye Li,et al.  A Genetic Algorithm for Job-Shop Scheduling , 2010, J. Softw..

[14]  Jan Karel Lenstra,et al.  Complexity of machine scheduling problems , 1975 .

[15]  Peigen Li,et al.  An effective hybrid genetic algorithm for the job shop scheduling problem , 2008 .

[16]  Rui Zhang,et al.  A hybrid immune simulated annealing algorithm for the job shop scheduling problem , 2010, Appl. Soft Comput..

[17]  Emanuel Falkenauer,et al.  A genetic algorithm for job shop , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[18]  Ihsan Sabuncuoglu,et al.  Job shop scheduling with beam search , 1999, Eur. J. Oper. Res..

[19]  Mitsuo Gen,et al.  A genetic algorithm with modified crossover operator and search area adaptation for the job-shop scheduling problem , 2005, Comput. Ind. Eng..

[20]  Hong Zhou,et al.  The hybrid heuristic genetic algorithm for job shop scheduling , 2001 .

[21]  Carlos A. Coello Coello,et al.  Use of an Artificial Immune System for Job Shop Scheduling , 2003, ICARIS.

[22]  Beatrice M. Ombuki-Berman,et al.  Local Search Genetic Algorithms for the Job Shop Scheduling Problem , 2004, Applied Intelligence.

[23]  Mitsuo Gen,et al.  Genetic Algorithms and Manufacturing Systems Design , 1996 .

[24]  Masayuki Yamamura,et al.  Genetic algorithm with search area adaptation for the function optimization and its experimental analysis , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[25]  Christian Bierwirth,et al.  An efficient genetic algorithm for job shop scheduling with tardiness objectives , 2004, Eur. J. Oper. Res..

[26]  B. Sakmann,et al.  The patch clamp technique. , 1992, Scientific American.

[27]  Tung-Kuan Liu,et al.  Improved genetic algorithm for the job-shop scheduling problem , 2006 .

[28]  Hyung Rim Choi,et al.  A hybrid genetic algorithm for the job shop scheduling problems , 2003, Comput. Ind. Eng..

[29]  Kagan Gokbayrak,et al.  Service Time Optimization of Mixed-Line Flow Shop Systems , 2010, IEEE Transactions on Automatic Control.

[30]  Tom V. Mathew.  Genetic Algorithm , 2022 .

[31]  S. Binato,et al.  A GRASP FOR JOB SHOP SCHEDULING , 2001 .

[32]  Yanchun Liang,et al.  Clonal Selection Based Memetic Algorithm for Job Shop Scheduling Problems , 2008 .

[33]  Ji Ma,et al.  ASP: An Adaptive Setup Planning Approach for Dynamic Machine Assignments , 2010, IEEE Transactions on Automation Science and Engineering.

[34]  Anupam Basu,et al.  A Tag Machine Based Performance Evaluation Method for Job-Shop Schedules , 2010, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.