• Siddhant Kumar
• NIdhi Sengar
• Prithvi Raj Chauhan

Supply Chain is a complex ecosystem of individuals, organizations, resources, activities, and technologies involved in the transformation of raw materials and constituent integrants into a consummate product that is delivered to the customers. A typical Supply Chain incorporates several processes; hence, there arises a need for optimisation of operations to achieve a precise modus-operandi that gets a good trade-off among different objectives like the quality of deliverables, cost of production and time of delivery. Several attempts have been made to implement multi-objective optimisation methods for the complications of Supply Chain Management. This study aims to deal with the logistic component of supply chain problem using modified Multi-Objective Non-dominated Sorting Genetic Algorithm-II (NSGA-II). In this paper, we attempt to minimize the total transportation cost and time. The problem is taken directly from the literature and a comparative study has been conducted in order to illustrate the performance of the presented model. The results show that the proposed modified algorithm is able to achieve a better Pareto-optimal solution as compared to the standard algorithm.

Supply Chain Management, NSGA-II, Multi-Objective Optimization, Artificial Intelligence

"MULTIOBJECTIVE OPTIMIZATION FOR SUPPLY CHAIN NETWORK USING ELITIST NON-DOMINATED SORTING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.542-548, April-2019, Available :http://www.jetir.org/papers/JETIR1904C89.pdf

"MULTIOBJECTIVE OPTIMIZATION FOR SUPPLY CHAIN NETWORK USING ELITIST NON-DOMINATED SORTING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp542-548, April-2019, Available at : http://www.jetir.org/papers/JETIR1904C89.pdf