Abstract
The green agri-food supply chain network (GASCN) design is critical to reduce the total transportation cost for efficient and effective supply chain management. This paper proposes a new solution based on particle swarm optimization (PSO) to find optimal solution for GASCN problem. PSO adopts transforming operator to modify particles in the population. The novelty of the transforming operator is that it can avoid applying the penalty function so that the diversity of populations is decreased. To show the efficacy of the algorithm, PSO is also tested on three cases. Results show that the proposed algorithm is promising and outperforms GA by both optimization speed and solution quality, especially when the scale of problem is large.
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Acknowledgments
This work is supported by the Special Funds for Doctoral Research Project of Guangdong University of Education under Grant No. 2012ARF05, the Natural Science Foundation of Guangdong Province of China under Grant No. S2012020011067 and the National High Technology Research and Development Program of China (863) under Grant No. 2012AA101701.
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Tao, Q., Huang, Z., Gu, C., Zhang, C. (2014). Optimization of Green Agri-Food Supply Chain Network Using Particle Swarm Optimization Algorithm. In: Wong, W.E., Zhu, T. (eds) Computer Engineering and Networking. Lecture Notes in Electrical Engineering, vol 277. Springer, Cham. https://doi.org/10.1007/978-3-319-01766-2_11
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DOI: https://doi.org/10.1007/978-3-319-01766-2_11
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