Genetic algorithm with new encoding scheme for job shop scheduling

In so many combinatorial optimization problems, job shop scheduling problems have earned a reputation for being difficult to solve. Genetic algorithm has demonstrated considerable success in providing efficient solutions to many nonpolynomial-hard optimization problems. In the field of job shop scheduling, genetic algorithm has been intensively researched, and nine methods were proposed to encode a chromosome to represent a solution. In this paper, we proposed a novel genetic chromosome-encoding approach; in this encoding method, the operation of crossover and mutation was done in three-dimensional coded space. Some big benchmark problems were tried with the proposed three-dimensional encoding genetic algorithm for validation and the results are encouraging.