1. Introduction
A practical model for optimizing scheduling in
commercial aquaculture has been demonstrated to be
capable of improving the productivity (total production
volume) of a commercial shrimp farm in Hawaii (Yu and
Leung, 2005). However, the ultimate measure of
economic viability of a commercial operation is its profit.
Profitability is part from productivity, but it is also
subjected to economic factors such as production costs
and market price. The purpose of this study is to extend Yu
and Leung's model to identify the most profitable, instead
of highest productivity, production schedule of a multipond
and multi-cycle commercial shrimp farm operating
in Hawaii. The other major extension of their model has to
do with the replacement of the constant growth chart with
an artificial neural network growth model. This extended
model is also used to elucidate the impact of major
biological and economic factors (e.g., survival, growth,
price seasonality and labor force constraints) on the
production schedule that optimizes profitability based on
possible scenarios expected by this farm.