Abstract: Aiming at the characteristics of complexity, constraint in discrete manufacturing workshop, in order to minimize the total energy consumption of the workshop as the target, discrete knowledge pigeons algorithm was proposed to solve discrete workshop energy efficiency optimization. In this algorithm, parameter knowledge was introduced into the optimization process to balance local search and global search, and the convergence and optimization ability of the algorithm were improved. The discrete process was added to the pigeons algorithm, which not only preserved the convergence and optimization ability of the algorithm, but also made the algorithm capable of dealing with discrete problems. Through the test of concrete examples, the particle swarm optimization, genetic algorithm and pigeons algorithm results were compared and analyzed, the pigeons algorithm in convergence and optimization ability is superior to the other two algorithms, which verifies the rationality and validity of the algorithm.

Key words: discrete manufacturing workshop, energy efficiency optimization, pigeons algorithm, knowledge parameters, second discrete process