Transgenetic algorithm: a new evolutionary perspective for heuristics design
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Bionic evolution based intrusion detection system
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Research on immune pathology in artificial immune system
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Expert Systems with Applications: An International Journal
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In our recent research, we showed results of the comparative study on effects of using several kinds of scheduling evaluation criteria as the fitness function of a genetic algorithm for job-shop scheduling. From these results, we obtained that the idle time criterion sometimes can provide a good makespan-minimizing schedule for a job-shop scheduling problem. In this paper, according to the above results, we propose a symbiotic genetic algorithm. The symbiotic genetic algorithm is structured with two kinds of evolution processes, i.e., (1) a co-evolution process in which both makespan and idle time schedule criteria are employed as the fitness functions into the operation-based genetic algorithm for job-shop scheduling, and (2) a sub-evolution process in which the total job waiting time schedule criterion is used as the fitness to provide high diversity for chromosome population. The symbiotic genetic algorithm tested on famous benchmark job-shop scheduling problems. Further, we introduce the concept of software system for job-shop scheduling based on the proposed method.