Optimised Job-Shop Scheduling via Genetic Algorithm for a Manufacturing Production System

The present work aims to develop a genetic algorithm (GA)-based approach to optimise the job-shop scheduling problem in a micro-brewery to minimise the production time and costs. In a production system, orders are placed randomly to form a queue. The problem is how to optimally schedule the tasks through the production process given the constraints on capacity and the customer satisfaction/service level. The work concentrates on formulating a mathematical model and to modify the scheduling problem based on a GA approach.

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