An evolutionary and genetic view of the job-shop scheduling problem

Unfortunately, one is still used to see the companies scheduling problems being addressed based on the experience. This type of approach, practically made by rough estimate becomes risky once it may lead to a sub-exploitation of the available resources (e.g. machinery, man power, raw materials), thus taking to the loss of profits by the part of the company and consequently making it difficult to expand and modernise. This type of scheduling never or rarely constitutes itself as the best solution, given the overwhelming number of variables to consider. These goals compete with each other originating conflicting situations, making the problem extremely complex, turning altogether impossible to reach acceptable solutions. In order to find a solution to these kind of problems, the goal of the present work is to study and implement the Job Shop Scheduling Problem using Genetic and Evolutionary Algorithms. Finally, a real situation, taken from the company Tipografia Tadinense Lda, where the goal is to minimise the total time that an order takes to be performed, having into account the format, the colour of the printing and the priority that each order has associated with, will be discussed.