Optimal management of agricultural systems

To remain competitive, many agricultural systems are now being run along business lines. Systems methodologies are being incorporated, and here evolutionary computation is a valuable tool for identifying more profitable or sustainable solutions. However, agricultural models typically pose some of the more challenging problems for optimisation. This chapter outlines these problems, and then presents a series of three case studies demonstrating how they can be overcome in practice. Firstly, increasingly complex models of Australian livestock enterprises show that evolutionary computation is the only viable optimisation method for these large and difficult problems. On-going research is taking a notably efficient and robust variant, differential evolution, out into real-world systems. Next, models of cropping systems in Australia demonstrate the challenge of dealing with competing objectives, namely maximising farm profit whilst minimising resource degradation. Pareto methods are used to illustrate this trade-off, and these results have proved to be most useful for farm managers in this industry. Finally, land-use planning in the Netherlands demonstrates the size and spatial complexity of real-world problems. Here, GIS-based optimisation techniques are integrated with Pareto methods, producing better solutions which were acceptable to the competing organizations. These three studies all show that evolutionary computation remains the only feasible method for the optimisation of large, complex agricultural problems. An extra benefit is that the resultant population of candidate solutions illustrates trade-offs, and this leads to more informed discussions and better education of the industry decision-makers.

Hydrothermal phase equilibria in Ln2O3-H2O-CO2 systems : I. The lighter lanthanides

Phase diagrams for Nd2O3-H2O-CO2 and Gd2O3-H2O-CO2 systems at 1500 atm are given along with the results of selected runs in La, Sm and Eu systems. The stable phases in systems of La and Nd, are Ln(OH)CO3-B, Ln2O2CO3-II and LnOOH, in addition to the Ln(OH)3 phase at extremely low partial pressures of CO2 in the system. The systems become more and more complex with decreasing ionic radi and the number of stable carbonate phases increases. Ln2(CO3)3 · 3H2O orthorhombic (tengerate-like phase) is stable from Sm to Gd in addition to the other phases. The Gd(OH)CO3-A (ancylite-like phase) is hydrothermally stable at XCO2 greater-or-equal, slanted 0.5 while its hexagonal polymorph, Gd(OH)CO3-B is stable at low partial pressures of CO2 in the system.