Mitsubishi Heavy Industries, Ltd. sometimes proposes a heat source configuration that combines multiple chillers that start, stop, and partial-load operate in certain cases. In such cases, there are a large number of options to select from when considering combinations of chillers of different capacities and models, and therefore finding a combination of equipment that minimizes costs while satisfying customer requirements needs experienced designers and takes a lot of time. To solve this issue, by applying an optimization technique that combines mathematical optimization and genetic algorithm, we realized a technology that can obtain the optimum equipment combination that meets customer requirements in a short time. We summarized the developed technology in this report.
