Some Concepts Of Green Supply Chain Management Using Particle Swarm Optimization Algorithm
DOI:
https://doi.org/10.48165/tjmitm.2020.1007Keywords:
Green warehouse, Green Supply Chain, Two-Green Agents, Environmental collaboration, Particle Swarm Optimization algorithmAbstract
Green Supply Chain management for green warehouse with environmental concerns a technique based on Particle Swarm Optimization algorithm to optimize inventory in the whole green supply chain. We focus on to specifically determine the dynamic nature of the excess stock level and shortage level required for inventory optimization in the green supply chain such that the total Green Supply Chain management for green warehouse with environmental concerns cost is minimized. The complexity of the problem increases when more products and multiple agents are involved in Green Supply Chain management for green warehouse with environmental concerns process that has been resolved in this work. Here, we are proposing an optimization methodology that utilizes the Particle Swarm Optimization algorithm, one of the best optimization algorithms, to overcome the impasse in maintaining the optimal stock levels at each member of the Green Supply Chain management for green warehouse with environmental concerns. We apply our method on four member of Green Supply Chain management for warehouse studied model for optimization.
References
Changdar, C., Mahapatra, G.S., and Pal, R.K. (2015) An improved genetic algorithm based approach to solve constrained knapsack problem in fuzzy environment Expert Systems with Applications, 42(4), 2276-2286.
Che, Z.H. and Chiang, C.J. (2010) A modified Pareto genetic algorithm for multi-objective build-to-order supply chain planning with product assembly Advances in Engineering Software, 41( 7–8), 1011-1022.
Dey, J.K., Mondal, S.K. and Maiti, M. (2008)Two storage inventory problem with dynamic demand and interval valued lead-time over finite time horizon under inflation and time-value of m oney European Journal of Operational Research, 185(1), 170-194.
Jawahar, N. and Balaji, A.N. (2009) A genetic algorithm for the two-stage supply chain distribution problem associated with a fixed charge European Journal of Operational Research, 194(2), 496-537.
Jawahar, N. and Balaji, A.N. (2012) A genetic algorithm-based heuristic to the multi-period fixed charge distribution problem Applied Soft Computing, 12(2), 682-699.
Jiang, Y., Chen, M. and Zhou, D. (2015) Joint optimization of preventive maintenance and inventory policies for multi-unit systems subject to deteriorating spare part inventory Journal of Manufacturing Systems, 35, 191-205.
Kannan, G., Sasikumar, P. and Devika, K. (2010) A genetic algorithm approach for solving a closed loop supply chain model: A case of battery recycling Applied Mathematical Modelling, 34(3), 655-670.
Narmadha, S., Selladurai, V. and Sathish, G. (2010) Multi-Product Inventory Optimization using Uniform Crossover Genetic Algorithm International Journal of Computer Science and Information Security, 7(1).
Priya, P. and Yakutia, K., Web based Multi Product Inventory Optimization using Genetic Algorithm International Journal of Computer Applications, 25(8).
Radhakrishnan, P., Prasad, V.M. and Gopalan, M.R. (2009), Inventory Optimization in Supply Chain Management using Genetic Algorithm International Journal of Computer Science and Network Security, 9(1).
Ramkumar, N., Subramanian, P., Narendran, T.T. and Ganesh, K. (2011) Erratum to “A genetic algorithm approach for solving a closed loop supply chain model: A case of battery recycling” Applied Mathematical Modelling, 35(12), 5921-5932.
Sharma, S., Yadav, A.S. and Swami, A. (2016) An Optimal Ordering Policy For Non-Instantaneous Deteriorating Items With Conditionally Permissible Delay In Payment Under Two Storage Management International Journal of Computer Applications, 140(4)
Singh, R.K., Yadav, A.S. and Swami, A. (2016) A Two-Warehouse Model for Deteriorating Items with Holding Cost under Inflation and Soft Computing Techniques International Journal of Advanced Engineering, Management and Science, 2(6).
Singh, S.R. and Kumar, T (2011). Inventory Optimization in Efficient Supply Chain Management International Journal of Computer Applications in Engineering Sciences 1(4).
Thakur, L and Desai, A.A. Inventory Analysis Using Genetic Algorithm In Supply Chain Management International Journal of Engineering Research & Technology, 2(7).
Wang, K.J., Makond, B. and Liu, S.Y. (2011) Location and allocation decisions in a two-echelon supply chain with stochastic demand – A genetic-algorithm based solution Expert Systems with Applications, 38(5), 6125-6131.
Yadav, A.S., Maheshwari P. and Garg A. (2016). Analysis of Genetic Algorithm and Particle Swarm Optimization for warehouse with supply chain management in inventory control”, Int. J. of Computer Appl. ,154(5), 10-17.
Yadav, A.S., Maheshwari P. and Garg A., Swami A. and. Kher, G. (2017), Modelling and analysis of supply chain management for deteriorating items with genetic algorithm and PSO”, Int. of Appl. or Innov. in Engg. and Mgmt., 6(6), 86-107.
Yadav, A.S., Maheshwari P. . Swami A. and Garg A. (2017), Analysis of six stages supplies chain management in inventory optimization for warehouse with artificial bee colony algorithm using genetic algorithm, Selforganizology, 4(3) 41-51,
Yadav, A.S., Maheshwari P. Swami A .and Kher G. (2017), Soft Computing optimization of two warehouse inventory model”, Asian J. of Mathematics and Computer research, 19(4), 214-223,
Yadav, A.S., Maheshwari P., Swami A. and Pandey G. (2018), A supply chain management for chemical industry for deteriorating items with warehouses using genetic algorithm, Selforganizology, 5(1-2) 1-9.
Yimer, A.D. and Demirli, K. (2010) A genetic approach to two-phase optimization of dynamic supply chain scheduling Computers & Industrial Engineering, 58(3), 411-422.
Zhang, H., Deng, Y., Chan, F.T.S. and Zhang, X. (2013) A modified multi-criterion optimization genetic algorithm for order distribution in collaborative supply chain Applied Mathematical Modelling, 37(14–15), 7855-7864.
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