Genetic algorithm approach to the solution of multi-purpose container loading and vehicle routing problems: Decision support system proposal in porcelain sector

The growing trade volume with the development of technology necessitates companies to use and to develop optimization practices in their operations. The speed, cost and accuracy of the operations that will be searched for a solution should be designed efficiently. Among the problems that the companies frequently encounter and need the solutions are container loading and vehicle routing problems. In particular, the decision support systems are needed in order to determine the priorities of the companies being in the porcelain sector in the workflow and delivery processes during the production, in order to execute them efficiently and effectively. When the designs for the different sectors are examined, it is seen that the solution suggestions produced by using artificial intelligence sub-branches such as expert systems, artificial neural networks, genetic algorithms and fuzzy logic are frequently used. In the literature, artificial intelligence-based decision support systems produced for the porcelain sector are seen in a very limited number and to be required in this field. In the porcelain sector, the production priorities vary due to the reasons such as profitability, customer satisfaction and storage constraints, and the optimization of decision support systems is important in the preference of the priority loading products in the shipment operations. In this study, it is aimed to produce more efficient solutions with the help of genetic algorithms for container routing and vehicle routing problems. In this way, it is aimed to minimize the number of containers used in the porcelain sector and the distance of vehicle routing. In the research, mathematical model was firstly formed based on total profit or delivery time priority in the container loading problem in the porcelain sector. The aim of the mathematical model was the total scalarization method. With the prepared software, suggestions have been made for the efficient and efficient loading of the products to the containers in accordance with the related purpose. In addition, in order to determine the shortest route during the distribution of the loaded container to the dealers or the stores, the method of finding the distance between two points was applied to the mathematical model and the solution was searched with genetic algoritm.