Effective Scheduling for Distributed Flexible Job Shop with Heterogeneous Production Lines

With the development of modern manufacturing and a rising inclination towards multiregional collaboration, distributed flexible job shop problem (DFJSP) is becoming an emerging topic in the domain of production optimization. In this study, a brand-new model of DFJSP with heterogeneous production lines (DFJSP-HPL) is formulated. Driven by small-to medium-size production runs in modern manufacturing, heterogeneous production lines (HPL) comprised of Bernoulli machines and finite buffers operate mainly under transients. Therefore, transient behaviors of heterogeneous production lines are investigated using Markov chain. An improved genetic algorithm (IGA) is adopted to address scheduling problem of DFJSP-HPL for minimizing makespan. Methods of encoding, decoding and genetic operators are designed to ensure that individuals consistently correspond to feasible scheduling throughout the iteration. The effectiveness of adopted IGA is demonstrated through computational experiments.