Using the Optimization Algorithm to Evaluate the Energetic Industry: A Case Study in Thailand

Abstract

Thailand’s economy is developing rapidly, with energy being a significant factor in this development. This study uses a variety of models to assess the performance of Thailand’s energy industry in two different phases, the first being from 2013 to 2017 and the second from 2018 to 2020. The Malmquist model-one of data envelopment required input and output data that showed Thailand’s productivity index and the rate-of-change ratio, which is used to assess technical changes, change efficiency, and productivity changes of the 12 listed companies in energetic generation and distribution in Thailand. To calculate future indicators, the forecast data are generated by applying the Grey model (1,1) GM(1,1). Accuracy prediction is determined by the mean absolute percentage error (MAPE). The results show that the magnitude of the change in efficiency during the first period is stable, and some major changes in the technical level of some companies may be observed. In the future, the performance of most companies has increased steadily, but performance has been outstanding. This research provides insights into Thailand’s energy over the past few years, and predictions of future performance may be used as a reference for more purposes.