Abstract
In this paper, single-machine scheduling with carbon emission index is studied. The objective function is to minimize the sum of total flow time and carbon emission. Firstly, the problem is shown to be NP-hard by Turing reduction. Then mathematical programming (MP) model is established. A pseudo-time algorithm based on dynamic programming (DPA) is proposed for small scale. And a Bird Swarm Algorithm (BSA) is proposed to compete with DPA. In addition, simulation experiments are used to compare the proposed algorithms. DPA is shown to be more efficient for small scale problem, and BSA is better for large scale problem.
Zaixing Sun
Ph.D
I am currently pursuing a PhD degree in computer science and technology with the School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China. I am also a visiting student with the Evolutionary Computation Research Group, Centre for Data Science and Artificial Intelligence & School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand. My research interests include cloud computing, intelligent optimisation and scheduling.