Extrapolation-Directed Crossover for Job-shop Scheduling Problems: Complementary Combination with JOX

In this paper, we propose a new Genetic Algorithm for JSP using two crossovers. The crossover, JOX, obtained relatively good results, however offspring generated by JOX exist around parents or within an intermediate area of them. This feature of JOX induces a convergence of the whole population. To deal with this fault of JOX, we propose a complementary combination of two crossovers. One is JOX, and the other, EDX, is our proposal. EDX is designed to have the population enlarge using a local search and explores the area where the population uncovers. Although a mutation is applied for exploration in general, we apply a framework of crossover to EDX for a more efficient exploration. The combination of two crossovers, which has a different search area, is able to compensate for each other's fault. The GA designed with these two crossovers was applied to large-size JSP benchmarks, and we show its effectiveness.

[1]  G. Thompson,et al.  Algorithms for Solving Production-Scheduling Problems , 1960 .

[2]  William J. Cook,et al.  A Computational Study of the Job-Shop Scheduling Problem , 1991, INFORMS Journal on Computing.

[3]  Christian Bierwirth,et al.  Control of Parallel Population Dynamics by Social-Like Behavior of GA-Individuals , 1994, PPSN.

[4]  Jan Karel Lenstra,et al.  A Computational Study of Local Search Algorithms for Job Shop Scheduling , 1994, INFORMS J. Comput..

[5]  N. Sannomiya,et al.  A new encoding scheme for solving job shop problems by genetic algorithm , 1996, Proceedings of 35th IEEE Conference on Decision and Control.

[6]  E. Nowicki,et al.  A Fast Taboo Search Algorithm for the Job Shop Problem , 1996 .

[7]  Takeshi Yamada,et al.  Job-Shop Scheduling by Simulated Annealing Combined with Deterministic Local Search , 1996 .

[8]  Hiroaki Satoh,et al.  Minimal generation gap model for GAs considering both exploration and exploitation , 1996 .

[9]  Isao Ono,et al.  A genetic algorithm for job-shop scheduling problems using job-based order crossover , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[10]  Isao Ono,et al.  A Real Coded Genetic Algorithm for Function Optimization Using Unimodal Normal Distributed Crossover , 1997, ICGA.

[11]  Y Takeshi,et al.  GENETIC ALGORITHMS FOR JOB-SHOP SCHEDULING PROBLEMS , 1997 .

[12]  I. Ono,et al.  A Genetic Algorithm Taking Account of Characteristics Preservation for Job Shop Scheduling Problems , 1998 .

[13]  M. Yamamura,et al.  A functional specialization hypothesis for designing genetic algorithms , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[14]  Shigenobu Kobayashi,et al.  An analysis of edge assembly crossover for the traveling salesman problem , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).