Attended home delivery in Indian public distribution system: an iterated local search approach

Abstract

Purpose In the modern era of e-grocery, attended home delivery (AHD) has been identified as a crucial part of the last-mile delivery problem. This paper aims to deal with a real-life last-mile-delivery problem in the context of the Indian public distribution system (PDS). The authors identified two different environments for the said AHD problem and proposed two different approaches to address the issue under these problem settings. Design/methodology/approach In this study, the authors first consider the problem in a static environment and propose an iterated local search (ILS) integrated with an adaptive large neighborhood search (ALNS) meta-heuristic algorithm to obtain a routing solution. Thereafter, they extend the study in a dynamic environment where new delivery requests occur dynamically and propose a heuristic algorithm to solve the problem. For the dynamic case, multiple scenarios for the occurrence of delivery requests are considered to determine decisions regarding the opportunity to include a new request into the current solution. Findings By computational experiments, the authors show that the proposed approach performs significantly well for large size problem instances. They demonstrate the differences and advantages of the dynamic problem setting through a set of different scenarios. Also, they present a comparative analysis to show the benefits of adopting the algorithm in dynamic routing scenarios. Research limitations/implications Future research may extend the scope of this study by incorporating stochastic delivery failure probabilities and customer behavior affecting the delivery response. Also, the present study does not take inventory policies at the depot into consideration. It will be of interest to see how the system performs under the uncertainty of supply from the depot. Despite the limitations, the authors believe that this study provides food for thought and encouragements for practitioners. Practical implications This study shows the benefits of adopting an AHD problem in a dynamic setting in terms of customer service as compared to a traditional static environment. The authors clearly demonstrate the differences and advantages of the dynamic problem setting through a set of different scenario analysis. Social implications This paper investigates a real-life AHD problem faced by the Department of Food, Supply and Consumer Affairs, India. The findings of this study will be of particular interest to the policy-makers to build a more robust PDS in India. Originality/value The study is unique and highly relevant for real-world applications and can help build a more robust AHD system. Also, the proposed solution approaches to aid the problem in both static and dynamic routing scenarios will be of particular interest to practitioners.

Attended home delivery under uncertain travel and response time: a case of Indian public distribution system

“…In this study, we extend the work of Chakraborty et al (2021) who were the first to propose the AHD in the Indian PDS in a multi-objective framework. The benefit of such a model was to enable the decision-maker to influence the decision either towards the overall cost minimization or a service level maximization.…”

“…Moreover, the duration of the delivery planning horizon to set out a delivery plan can also play a significant role in nonprofit systems like Indian PDS. This has not been studied in any of the existing literature on AHD, including Chakraborty et al (2021). Furthermore, to the best of our knowledge, none of the existing literature considered the impact of travel time and customer response time simultaneously on an AHD problem, which can impact the overall cost-performance over a fixed planning horizon.…”

“…However, their work was primarily focused on the development of a dynamic ordering strategy in Indian PDS and demonstrated the relative benefits of the same compared to a static environment. Similar to most of the existing literature in AHD, Chakraborty et al (2021) also considered a deterministic routing environment where travel times and customer response times are well known. However, these deterministic assumptions do not always hold true and thus lead to infeasible route planning and excess over-time wages.…”

“…However, these deterministic assumptions do not always hold true and thus lead to infeasible route planning and excess over-time wages. Chakraborty et al (2021) also did not consider over-time in their proposed model, which acts as a major limitation to their study. Moreover, the duration of the delivery planning horizon to set out a delivery plan can also play a significant role in nonprofit systems like Indian PDS.…”

Designing a drone assisted sample collection and testing system during epidemic outbreaks

“…For the current problem, we propose a genetic algorithm-based approach integrated with a local search technique to effectively search the solution space. For real-world applications, the local search algorithm is also very well-established due to its ability to escape the local-optimal-trap without losing many of the good properties of the current solution (Chakraborty et al , 2021). In designing such a system, “exploration” refers to the process of exploring potential regions of the solution space to quickly identify the global optima.…”