Modified Intelligent Water Drops with perturbation operators for atomic cluster optimization

A modified version of the Intelligent Water Drops algorithm (MIWD) was developed then used to determine the most stable configurations of Lennard-Jones (LJ), Binary Lennard-Jones (BLJ) and Morse Clusters. The algorithm is unbiased in that it uses no a priori cluster geometry information or cluster seeds. Results for LJ clusters show that the algorithm is effective and efficient in rediscovering all clusters up to size N = 104 with better success rates specially on difficult clusters compared to previous best methodologies reported in literature. Results on more difficult systems, such as the Binary Lennard Jones clusters up to size 50 (with 5 different atomic size ratios) and Morse clusters up to size 60 (with 2 interparticle range potentials), also showed the ability of MIWD to handle more complex systems. MIWD was then applied to predict the most stable structures of Janus clusters up to size 50 and on size 100 using a LJ potential model with a modulated angular term suited for two-patched Janus particles. Results show that MIWD is able to find well-structured geometries of Janus clusters. It is believed that this has been the first time that a nature-inspired stochastic algorithm and a variant of the IWD algorithm has been applied to the configurational optimization of Janus clusters

An Optimization Model for Processed Food-grade Flour from Off-grade Cavendish Banana Supply Chain Network Design

One of the fundamental issues in Philippine agriculture is the low income of small-scale farmers of Cavendish banana despite the increasing demand for it. The AMS Employees’ Fresh Fruits Producers Cooperative (AMSEFFPCO), for instance, was observed to generate unpleasing profit in the production process of converting off-grade Cavendish banana into food-grade flour. We hypothesized that the profit may be increased by determining the optimal number of components of the production process, i.e., the number of delivery trucks and mills to be operated, as well as the number of nonregular (e.g., peelers, washers) and regular laborers (e.g., slicers, dryers) to be hired. From the constructed supply chain network design of the production process, we formulated and solveda mixed integer linear programming model to obtain the optimal values of the components. Our findings showed that the profit of the cooperative can be maximized if they operate two trucks and one mill and hire nine nonregular laborers and fourteen regular laborers. Moreover, we also studied how the changes in the volume of supplied off-grade bananas affect the values of the optimal components of the supply chain. By implementing the results of this study, the cooperative is expected to generate approximately PhP 9000 per batch delivery, i.e., 4000 kg of off-grade bananas. The methodology developed in this study can also be applied in other banana producer’s organization with similar supply chain network

Modelling the Allocation of Cavendish Bananas into Enterprises of Small-scale Farmers

Changes that occurred in the agriculture food system pose challenges to small-scale Cavendish banana farmers in terms of their vulnerability and ability to survive. The current challenges can be addressed by increasing the opportunities available to small-scale farmers in order to increase their profits. The current system of the farmers is to allocate their entire land into either the contractual market or the spot market. Although these farmers can also venture into processing raw bananas into an alternative product such as banana flour, the participation of farmers to embark on such enterprise is minimal. Hence, we formulated mathematical models to explore via model simulation how a farmer’s profit varies with different proportions of harvested bananas to be allocated simultaneously into three enterprises, namely, the contractual market, the spot market, and the banana flour market. Varying selling rates were also investigated to see the profitability potential of each enterprise. Our findings showed that (1) it is best to allocate >75% of the harvested bananas in the contractual market when it has 100% selling rate while the other enterprises have ≤10% selling rates; (2) the farmer can gain the highest profit when the selling rate of the spot market is high; and (3) even without allocation to the spot market, the food-grade banana flour market has a potential role in increasing the profit of the farmer by ≥6% for every 10% increase in its a location. Insights from different model scenarios will aid farmers in making decisions on where to allocate harvested bananas under uncertain selling rates