Multi-objective Parallel-machine Scheduling Problem Considering Energy Consumption and Deteriorating Effect

In actual manufacturing process, a great deal of energy resources is employed. Therefore, decision-makers have to not only consider time-oriented objectives, but also focus on energy-efficient criteria. In our work, we study the energy-efficient problem of the parallel machine scheduling with uncertain factor, i.e., deteriorating effect. And a mathematical model to reach minimization makespan and energy consumption is formulated. Then, we design an approach of multi-objective ant lion optimization according to the characteristics of this work. By conducting extensive simulation experiments, this work compares ant lion optimization approach with two popular multi-objective evolutionary algorithms. And two performance indexes of coverage metric and inverted generational distance are employed to analyze their results of the experiment. The comparative results indicate that the better solutions can be found by ant lion optimization approach for solving our concerned problem.