Solving Location Based Inventory Routing Problem in E-Commerce Using Ant Colony Optimization - Challenges and Opportunities in the Digital Era Access content directly
Conference Papers Year : 2018

Solving Location Based Inventory Routing Problem in E-Commerce Using Ant Colony Optimization

Abstract

In the current era of digitization and the rise of e-commerce sector over the past decade, it becomes essential to identify and address issues surrounding e-commerce logistics. The current study addresses the problem of location based inventory routing for delivery from warehouse to various destinations. The study uses a dynamic meta-heuristic approach, Ant Colony Optimization (ACO), to solve this problem in e-commerce. A sensitivity analysis is done to identify the coefficient values to be fixed for the ACO Engine. The longitude and latitude coordinates from Google Maps are mapped to distance metrics between the warehouse and the delivery destinations for orders to be delivered on a particular day. The analysis is conducted for a total of 346 locations and the total distance to be travelled came out to be 690.29 km using the proposed approach. Findings of the study can be applicable in multiple domains of e-commerce logistics and other graph based routing problems.
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hal-02274181 , version 1 (29-08-2019)

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Reema Aswani, Arpan Kumar Kar, P. Vigneswara Ilavarasan, Rohan Krishna. Solving Location Based Inventory Routing Problem in E-Commerce Using Ant Colony Optimization. 17th Conference on e-Business, e-Services and e-Society (I3E), Oct 2018, Kuwait City, Kuwait. pp.557-566, ⟨10.1007/978-3-030-02131-3_48⟩. ⟨hal-02274181⟩
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