An Investigation of Quality Enhancement in Online Shopping and Inventory Maintenance
N. Jayakanthan1, M. Manikantan2, R. Rassika3
1N. Jayakanthan, Assistant Professor SRG Masters, Department of Computer Applications, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
2M. Manikantan, Assistant Professor SRG Masters, Department of Computer Applications, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
3R. Rassika, Masters, Department of Computer Applications, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 12 December 2018 | Revised Manuscript received on 23 December 2018 | Manuscript Published on 09 January 2019 | PP: 217-219 | Volume-7 Issue-4S November 2018 | Retrieval Number: E2035017519/19©BEIESP
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Abstract: Online shopping is the culture of current e-commerce scenario. It provides lot of choices and opportunities. Every day million of transactions are performed and billion dollars are traded. But the major drawback of online shopping system is latency in order fulfillment and inventory management. There is a imperative for a system to address the time efficiency of the above process. To improve the performance of online commerce here with we propose a model called “Shoppy Do”. The Bee colony optimization modes performs stock clustering. The Pathrouter, a greedy algorithm is used to optimize the short path to improves the efficiency. The proposed model address the latency issues in order fulfillment.
Keywords: E-Commerce, Efficiency, ACO Algorithm, Resource Allocation.
Scope of the Article: Online Learning Systems