A multi-objective memetic optimization approach for green transportation scheduling

This research develops an evolution strategy-based multi-objective optimization approach to handle a green transportation scheduling problem with some distinct realistic features. The problem is formulated as a bi-objective mixed integer nonlinear program. The effectiveness of the proposed approach is evaluated by numerical experiments based on industrial data. Experimental results demonstrate that the proposed approach can solve the investigated problem effectively.