Genetic algorithm based novel methodology of multi-constraint job scheduling

An intelligent production system entails flexibility and adaptability to the dynamic and variable environment. In this regard, scheduling flexibility is a core element. Tons of literature has been published in the production domain, however, less attention has been paid to the solution of flexible job shop scheduling problems with multi constraints. This paper proposes a novel genetic algorithm based solution which involves multiple products parallel scheduling, capacity constraints and uncertain production cycle. Feasibility and effectiveness of the proposed algorithm has been validated through experimental results.