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In recent years, with increased size of the manned space program and systems used in the programs, the role of computer simulations has increased. I have long used and developed independently several simulation tools for the design, operation, analysis, and optimization of the Life Support Systems (LSS). I recognized that the designer makes his/her own idea certain while building a simulation model on a computer. However, conventional simulation tools are not designed so that the interaction between the designer and a model building support environment is dynamically used to bring out a designer's idea. Therefore, in this paper, I consider the development of a conceptual design support tool in the design of the LSS, while focusing attention on the interaction between the simulation tool and the designer.

We developed an Advanced Life Support systems scheduler (ALS scheduler) to back up the habitation experiments of Closed Ecology Experiment Facilities (CEEF), and integrated the Lagrangian decomposition and coordination method for a scheduling algorithm of the scheduler. Later research revealed that when comparing solutions obtained by the Lagrangian decomposition and coordination method and by a skilled operator, respectively, a schedule sought by the skilled operator has different features from those of a schedule sought by the Lagrangian decomposition and coordination method. This paper describes how to generate a schedule such as one created by a skilled operator, while reducing complexity by integrating empirical knowledge to the Lagrangian decomposition and coordination method.

A habitation experiment using the Closed Ecology Experiment Facilities was started in 2005. In the future, the stays will be gradually extended. We have been developing the three layered control software for a Control Computer System of the Closed Ecology Experiment Facilities in order to back up the habitation experiments. In this paper, we will show the development of an operation scheduling system for one of the three layers, such as at the planning and scheduling level, and discuss the development of a scheduling algorithm that does not cause the complexity of the ALS scheduler to be exponentially increased.