A Three-Dimensional Encoding Genetic Algorithm for Job Shop Scheduling

Abstract

In so many combinatorial optimization problems, job shop scheduling problems have earned a reputation for being difficult to solve. GA has demonstrated considerable success in providing efficient solutions to many non-polynomial-hard optimization problems. In the field of job shop scheduling, GA has been intensively researched, and there are nine kinds of methods were proposed to encoding 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. 5 selected benchmark problems were tried with the proposed three- dimensional encoding GA for validation and the results are encouraging.