Energy Saving Scheduling of A Single Machine System Based on Bi-objective Particle Swarm Optimization*

Energy cost becomes an important performance indicator of a production process. A great deal of energy is wasted because of the idle period resulted from the unreasonable schedule of jobs and machines. Energy consumption and other performance indicators should be combined to optimize the production schedule in shop floor. A single machine scheduling optimization problem is considered in this study, where assume that jobs are arrived at different time. An optimization model with bi-objective is formulated for minimizing the total energy consumption and the total tardiness during a shift production. Based on sequence encoding of job-machine schedule in two dimensions, a particle swarm optimization method is proposed to search Pareto solutions of the model. External archive technology is adopted to store and maintenance the non-dominated schedules. A grid density method is used to update the global best solution so far for the construction of the next generation populations. A case study is given to show the effectiveness of the algorithm based on the Pareto solutions.