Empirical Performance Evaluation of a Parameter-Free GA for JSSP

The job-shop scheduling problem (JSSP) is a well known di.cult NP-hard problem. Genetic Algorithms (GAs) for solving the JSSP have been proposed, and they perform well compared with other approaches [1]. However, the tuning of genetic parameters has to be performed by trial and error. To address this problem, Sawai et al. have proposed the Parameter-free GA (PfGA), for which no control parameters for genetic operation need to be set in advance [3].