2022 Volume 65 Issue 3 Pages 138-155
We consider an air conditioning system design that minimizes the costs of electricity and equipment, while satisfying individual usage requirements. The problem of finding an optimal configuration can be formulated as a combinatorial optimization problem. When the cost of electricity is evaluated using simulation software, computational time is excessive. We therefore propose an efficient iterated local search method that uses sparse estimation and extreme statistics to reduce the computational time for evaluating the cost of electricity, and which makes use of the information obtained during a local search. In addition, Thompson's update probability is used for effective neighborhood selection.
