Multiobjective fuzzy vehicle routing using Twitter data: Reimagining the delivery of essential goods

Abstract

The world faced a major disruption in the form of the coronavirus disease (COVID-19) pandemic, which caused many countries to impose severe restrictions on movement, popularly known as "lockdown." These lockdowns impacted transportation adversely, leading to massive disruptions in global and local supply chains. As the local markets were shut down, more people started turning to e-commerce logistics platforms offering doorstep deliveries of essential items (food and medicines). This resulted in an explosion in demand for such services, and businesses struggled to complete their deliveries. Additionally, the volume of real-time text data suddenly increased, as these customers started sharing their feedback on social media platforms. The availability of real-time raw text data and its popularity for solving complex business problems motivated the development of the approach proposed herein to address last-mile delivery issues.Thus, this paper suggests the use of Twitter data to identify the various grievances of customers about e-commerce logistics platforms. Natural language processing, a popular tool for text analytics, is employed to extract consumer tweets from the Twitter profiles of such businesses and subsequently to clean, process, and analyse them. Issues are categorized and used as objectives in a multiobjective fuzzy vehicle routing problem (VRP). An integrated hybrid fuzzy VRP is developed and coded to solve last-mile delivery issues. Experimental results and comparative analyses highlight the benefits of the novel approach. Managerial insights and scope for future research assist in the further development of the idea.

Vehicle Routing Optimization for Pandemic Containment: A Systematic Review on Applications and Solution Approaches

“…Multiple objectives: As presented in Table 7, multiple objectives were discussed in a range of articles. Most of these papers adopted a decomposition-based algorithm to transform multi-objectives into one equivalent objective, and the weight of each goal in the objective function can be derived from min-max normalization [70], ML [85], and the decision maker's experience [66,67,84,85,95]. Note that only one work introduced dynamism in the weights, which were dependent on the real-time information of customers' request [85].…”

“…Most of these papers adopted a decomposition-based algorithm to transform multi-objectives into one equivalent objective, and the weight of each goal in the objective function can be derived from min-max normalization [70], ML [85], and the decision maker's experience [66,67,84,85,95]. Note that only one work introduced dynamism in the weights, which were dependent on the real-time information of customers' request [85]. Other decomposition-based methods such as Chebyshev method [52], Membership function [82] and Goal Programming(GP) [77,81,105] were also utilized to construct a compromising model for solving multi-objectives problems.…”

“…This finding makes sense, given the importance of using pharmaceutical interventions to control the pandemic. In addition, nine articles examined e-commerce logistics services, such as fresh food shipping [69,89,102] and parcel delivery [85,86,90,100,103,106], while four papers referred to on-demand transportation services [70,104,108,109], the use of which has been accelerated by the onset of COVID-19 in urban areas [92]. Among the rest of the articles in this area, one focused on oil distribution and one focused on ready meal delivery in hotels.…”

“…Among fourteen articles that took multiple sustainable factors into account, only six aimed to minimize the emission of pollutant gas together with other objectives. These studies addressed the problem of waste collection [105], parcel delivery [85,90], food distribution [109], and medical supplier transportation [52,92]. The other seven studies concerned with both cost and social factors.…”

“…In order to lessen the effect of the COVID-19 pandemic while also ensuring the availability of critical supplies in the last mile, various contactless delivery strategies have been proposed. Among these, home delivery [69,85,89,108] is a critical consideration in the case of lockdown, where goods are distributed to the designated location and customers pick them up themselves [52,69,108]. In addition, self-driving delivery robots have been used to avoid person-to-person contact [87,104,106,107].…”