Developing Crew Allocation System for the Precast Industry Using Genetic Algorithms

The Precast Concrete Industry (PCI) is one of the major contributors to the national economy and can be categorised as labor-intensive industry. It is currently experiencing shortcomings in terms of delivery products at a competitive cost and time. This is mainly due to the inefficiencies associate with planning and scheduling of skilled operators within crews configurations. This paper presents a new strategy for efficient allocation of crews of workers in the precast concrete industry using Genetic Algorithms-based simulation modeling. The aim of this study is to develop crew allocation system that can efficiently allocate possible crews of workers to precast concrete labor-intensive repetitive processes. Genetic Algorithms (GAs) have been developed to solve this type of problems. Process mapping methodologies were used to identify and document the processes involved in producing precast components. Then process simulation was