Vehicle Routing Problem For Express Delivery In An Khang Pharmacy Retail Chain

Abstract

The pharmaceutical industry faces unique challenges in the management of medicines and dietary supplements due to their short product lifecycles, small size, lightweight, and requirement for precise temperature and humidity control during transit. Additionally, the widespread use of cutting-edge technology has changed how consumers engage with pharmacies, driving a requirement for effective information collecting and communication. To address these complexities, logistics companies operating in the pharmaceutical sector often utilize various types of vehicles with different carrying capacities. When maximizing their service delivery, these businesses must carefully consider both fixed and variable expenses, making vehicle assignment and route optimization difficult. This paper focuses on solving the complex problem of multi-type vehicles and mixed-integer programming route optimization while adhering to distribution time and carrying capacity constraints. The study proposes the use of a hybrid particle swarm intelligence (PSI) heuristic approach, which incorporates crossover and mutation operators from genetic algorithms and integrates a 2-opt local search strategy. This approach is applied to the case of An Khang Pharmacy, a prominent pharmacy retailer in Ho Chi Minh City. This study evaluates the efficiency of the suggested algorithm through a thorough examination utilizing An Khang Pharmacy as a case study. The findings of this study offer useful information for improving transportation logistics in the pharmaceutical sector. The use of this algorithm may enhance order fulfillment, cost-effectiveness, and general customer pleasure, which will eventually be advantageous to pharmaceutical businesses and their clients