Mathematical programming model is effective to both farm planning and managerial evaluation of the farming-systems. With models that consider precipitation risk, however, it is time consuming to calculate workable machinery times based on hourly precipitation data. In this paper, we propose a decision support program (DSCP) to help researchers more easily construct mathematical programming models under the constraints of workable machinery times, and to more efficiently obtain optimal solutions under each pattern of workable machinery time constraints than is possible with existing systems. The DSCP can calculate workable machinery times on a five- or ten-day basis in the production seasons by using hourly precipitation data, which have no restriction on duration, in each target area. The DSCP can also automatically add the constraints of workable machinery times to the last row of the simplex tableau. Moreover, the DSCP can estimate the optimal solution of a mathematical programming model under workable machinery time constraints consistent with XLP, which is a linear programming tool for farm planning. The DSCP estimates optimal solutions of the model that depend on each pattern of workable machinery time constraints at once, and comparatively analyzes these optimal solutions. A case study suggests that the DSCP provides more precise workable machinery times over longer periods, and obtains more accurate optimal solutions of farm planning than can existing decision support programs for farm planning.

Feral raccoons have become a big problem in Osaka Prefecture (causing agricultural damage, invading houses, etc.). In this study, we used system dynamics to predict the population dynamics of raccoons in Osaka. We constructed four population dynamics models incorporating the parameters of initial number of individuals and the mortality rate, and we simulated population dynamics from 2004 to 2007. Each of the four models indicated that the population of raccoons would increase. Then, using the model and parameters that best matched the past research, we simulated population dynamics from 2007 to 2027. To exterminate the raccoon, our modelling showed to have to put 1.5 times or more the capture pressure from the number of harmful wildlife control in at least 2007.