Multiobjective Hybrid Genetic Algorithms for Manufacturing Scheduling: Part II Case Studies of HDD and TFT-LCD

Abstract

Manufacturing scheduling is one of the most important and complex combinatorial optimization problems, where it can have a major impact on the productivity of a production process. Moreover, most of manufacturing scheduling problems fall into the class of NP-hard combinatorial problems. In this paper, we introduce how to design hybrid genetic algorithms (HGA) and multiobjective hybrid genetic algorithms (Mo-HGA) for solving practical manufacturing scheduling problems for the hard disc device (HDD) and the thin-film transistor-liquid crystal display (TFT-LCD) manufacturing systems, respectively. In particularly, evolutionary representations and the fitness assignment mechanism as well as the hybrid genetic operations are introduced. Through a variety of computational experiments, the effectiveness of these HGA algorithm for HDD and Mo-HGA algorithm for TFT-LCD module assembly as the practical manufacturing scheduling problems are demonstrated. This paper introduces how to design Mo-HGAs for solving the practical multiobjective manufacturing scheduling problems expanded by a multiobjective flexible job-shop scheduling problem (Mo-FJSP; operation sequencing and resources assignment).