Intelligent Vehicle Scheduling and Routing for a Chain of Retail Stores: A Case Study of Dhaka, Bangladesh

M. Azizur Rahman, Al-Amin Hossain, Binoy Debnath, Zinnat Mahmud Zefat, Mohammad Sarwar Morshed and Ziaul Haq Adnan
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M. Azizur Rahman: Department of Mechanical and Production Engineering, Ahsanullah University of Science and Technology, Dhaka 1208, Bangladesh
Al-Amin Hossain: Department of Mechanical and Production Engineering, Ahsanullah University of Science and Technology, Dhaka 1208, Bangladesh
Binoy Debnath: Department of Mechanical and Production Engineering, Ahsanullah University of Science and Technology, Dhaka 1208, Bangladesh
Zinnat Mahmud Zefat: Department of Mechanical and Production Engineering, Ahsanullah University of Science and Technology, Dhaka 1208, Bangladesh
Mohammad Sarwar Morshed: Department of Mechanical and Production Engineering, Ahsanullah University of Science and Technology, Dhaka 1208, Bangladesh
Ziaul Haq Adnan: Department of Management, North South University, Dhaka 1229, Bangladesh

Logistics, 2021, vol. 5, issue 3, 1-21

Abstract: Background : Retail chains aim to maintain a competitive advantage by ensuring product availability and fulfilling customer demand on-time. However, inefficient scheduling and vehicle routing from the distribution center may cause delivery delays and, thus, stock-outs on the store shelves. Therefore, optimization of vehicle routing can play a vital role in fulfilling customer demand. Methods : In this research, a case study is formulated for a chain of retail stores in Dhaka City, Bangladesh. Orders from various stores are combined, grouped, and scheduled for Region-1 and Region-2 of Dhaka City. The ‘vehicle routing add-on’ feature of Google Sheets is used for scheduling and navigation. An android application, Intelligent Route Optimizer, is developed using the shortest path first algorithm based on the Dijkstra algorithm. The vehicle navigation scheme is programmed to change the direction according to the shortest possible path in the google map generated by the intelligent routing optimizer. Results : With the application, the improvement of optimization results is evident from the reductions of traveled distance (8.1% and 12.2%) and time (20.2% and 15.0%) in Region-1 and Region-2, respectively. Conclusions : A smartphone-based application is developed to improve the distribution plan. It can be utilized for an intelligent vehicle routing system to respond to real-time traffic; hence, the overall replenishment process will be improved.

Keywords: route optimization; intelligent application; Android Studio 4.0; Google Sheet; Dhaka city map (search for similar items in EconPapers)
JEL-codes: L8 L80 L81 L86 L87 L9 L90 L91 L92 L93 L98 L99 M1 M10 M11 M16 M19 R4 R40 R41 R49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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