Minimizing the total cost of hen allocation to poultry farms using hybrid Growing Neural Gas approach

• The traditional Growing Neural Gas (GNG) was used for clustering hen houses by considering distance only.
• To improve the solutions, we developed the hybrid GNG by considering both distance and weights of hen house sizes.
• Routes determination to allocate hens to the hen houses was also carried out in order to minimize the total distance.
• The maximum allowable difference of ages of hens in the same hen house is considered as occurred in real practices.
• We proposed the multi-time period clustering based on chick ordering and hen house capacities.

In this paper a decision support system to solve the problem of hen allocation to hen houses with the aim of minimizing the total cost is described. The total cost consists of farm utilization cost, hen transportation cost, and loss from mixing hens at different ages in the same hen houses. Clustering of hen houses using the traditional Growing Neural Gas (GNG) was first determined to allocate hens to the hen houses effectively. However, the traditional GNG often solves the clustering problem by considering distance only. Therefore the hybrid Growing Neural Gas (hGNG) considering both the distance from the centroids of the clusters to the hen houses and the weights of hen house sizes was proposed to solve the problem. In the second phase, allocating and determining routes to allocate hens to the hen houses using the nearest neighbor approach were carried out in order to minimize the total distance. The performance of the algorithm was measured using the relative improvement (RI), which compares the total costs of the hGNG and GNG algorithms and the current practice. The results obtained from this study show that the hGNG algorithm provides better total cost values than the firm’s current practice from 7.92% to 20.83%, and from 5.90% to 17.91% better than the traditional GNG algorithm. The results also demonstrate that the proposed method is useful not only for reducing the total cost, but also for efficient management of a poultry production system. Furthermore, the method used in this research should prove beneficial to other similar agro-food sectors in Thailand and around the world.