This paper present the development of a Genetic Algorithm (GA) for optimisation of precedence-constrained
production sequencing and scheduling problems. This class of problems requires a double optimisation - for sequencing and
scheduling - at the same time. Due to nature of constraints, novel strategies for encoding chromosomes, crossover,
mutation operations and handling constraints have been developed. The GA developed to solve this class of problems
uses variable length chromosomes and its capability is demonstrated using a complex and realistic case study. The
result obtained for the case study shows that the proposed GA is applicable to real-life precedence-constrained production
sequencing and scheduling optimisation problems, which are ubiquitous to production and manufacturing environments.

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