Relief Supply Chain Research Articles

A novel two-stage stochastic programming model to design an integrated disaster relief supply chain network-a case study

A novel two-stage stochastic programming model to design an integrated disaster relief supply chain network-a case study

Optimizing Reserve Decisions in Relief Supply Chains with a Blockchain-Supported Second-Hand E-Commerce Platform

Optimizing Reserve Decisions in Relief Supply Chains with a Blockchain-Supported Second-Hand E-Commerce Platform

A viable relief supply chain network design by considering risk and robustness for disaster and crisis management

A viable relief supply chain network design by considering risk and robustness for disaster and crisis management

Toward a More Diverse and Equitable Food Distribution System: Amplifying Diversity, Equity and Inclusion in Food Bank Operations

This article provides an evidence-based discussion of an ongoing effort within the operations of hunger relief organizations to address diversity, equity, and inclusion (DEI) by sourcing and distributing more culturally relevant food. Through nearly 100 interviews with food bank personnel in diverse roles (from partner agency relations to executives) representing various regions of the United States, we explore the challenges faced by different functional units within the organization. These interviews indicate a shift to more inclusive language, more personalized metrics, and more inclusive operations. We critically analyze the related literature and identify opportunities for infusing DEI practices in the study of hunger relief supply chains.

A data-driven robust decision-making model for configuring a resilient and responsive relief supply chain under mixed uncertainty

A data-driven robust decision-making model for configuring a resilient and responsive relief supply chain under mixed uncertainty

Disaster relief supply chain network planning under uncertainty

Disaster relief supply chain network planning under uncertainty

Comparative study of robust optimization model of multimaterial emergency logistics in an uncertain environment

AbstractGiven the significance of objective functions in alleviating human suffering within the humanitarian relief supply chain, it is imperative to consider both logistics costs and the cost of deprivation as ideal targets. This study investigates a multimaterial single‐cycle stochastic mixed integer model, integrating uncertainties about post‐disaster demand, supply survival, and road networks. An innovative heuristic approach is used to solve the stochastic facility location problem, which minimizes unfulfilled requests and response times in lexicographic order. This research also compares the cost‐minimization model of the pre‐positioning problem to an alternative model that maximizes demand satisfaction under resource constraints. Empirical validation through numerous case studies and solutions confirms the effectiveness and feasibility of the alternative model. The results of our experiments consistently demonstrate that the best solution provided by the alternative model not only satisfies the minimum cost model but also surpasses the conventional problem, without compromising performance. Consequently, it is crucial to avoid the cost‐minimization approach at the expense of human suffering.

An integrated production and distribution model for the supply of relief kits in flood relief supply chains

An integrated production and distribution model for the supply of relief kits in flood relief supply chains

Blockchain-enabled Safeguard Mechanism in SCP-based Relief Supply Chain Designs in Response to Long-term Disasters

Blockchain-enabled Safeguard Mechanism in SCP-based Relief Supply Chain Designs in Response to Long-term Disasters

The efficacy of e-procurement systems towards enhancing agility of relief development and protection programs; a case study of Benjamin Mkapa Foundation (BMF) Dares Salaam -HQ Office

The aim of this study was to examine the effects of E-procurement on Disaster Relief Influencing Supply Chain Performance in Relief Development and Protection Organization. Specific objectives of this study were to assess the effect of E-tendering, E-catalogues and E-sourcing on disaster relief SCP at BMF Dar es Salam. The study used quantitative research design. The study employed positivism research paradigm. Non parametric measurement was used to measure study variables. Questionnaires and documentary review were used as data collection methods. A sample of 44 staff was drawn from a targeted population of 50 staff. Data was collected using questionnaire instrument were subjected to Statistical Package for Social Science (SPSS v.22) for running the quantitative analysis technique. Data was analysed using descriptive and inferential statistics. Based on objective study found that information sharing has insignificant effect while e-procurement and staff competence have significant effect on SCP. Based on the findings, the findings revealed that electronic procurement has great effect on disaster relief supply chain performance at BMF. The results revealed that BMF has procurement system that enable emergency procurement and availability of victims needs during disaster, BMF use e-tendering to enhance bulk availability of victims needs during disaster, and BMF embraced the use of procurement system in all procurement functions. Also, BMF procurement system is well integrated with supply chain systems. Finally, use e-sourcing to enable on time availability of victims needs during disaster at BMF. Multiple regression. The study came up with following recommendations; BMF should build capacity, training and development in technology (e-procurement); and policymaker should use these findings as essential tool to promote disaster relief supply chain performance in Tanzania.

Pre-positioning and procurement strategy for relief supplies with the critical raw material participation

The supply disruption of the critical raw material and the manufacturer’s pre-disaster insufficient relief supply reserves significantly affect the relief supply chain system. To solve this dilemma, we divide the demand for relief supplies into critical and non-critical periods according to relief time and urgency requirements, and propose the manufacturer’s physical reserve and production capacity reserve strategies for relief supplies. Then we develop the Benchmark model with only a single physical reserve strategy. In particular, a Dual reserve model and a Three-tier relief supply chain model are developed, and the optimal decisions for the government and the agreement enterprises are obtained. Through a comparative analysis between the Dual reserve model and the Benchmark model, the manufacturer tends to adopt a dual reserve strategy with both real products and production capacity as it can strengthen the government’s capacity for emergency response and support while diminishing the manufacturer’s inventory risk. And the Three-tier relief supply chain model with the participation of the critical raw material supplier proves to be better than the Dual reserve model since it reduces the overall cost of the supply chain and guarantees the source of critical raw materials for post-disaster relief supply production.

An IoMT platform for an integrated sustainable energy-efficient disaster relief supply chain to prevent severity-driven disruptions during pandemics

Pandemics, such as the Influenza virus and the contemporary COVID-19, can lead to widespread disruptions in key segments, including the supply chain, beyond the capacity of communities or governments. The establishment of a robust relief supply chain network can alleviate the destructive effects of pandemics and strengthen the distribution of relief supplies across medical centers and demand zones. Furthermore, the Internet of Medical Things (IoMT), which connects medical devices and applications over the internet, provides healthcare providers with real-time data collection, transmission, and sharing. Considering this motivation, in this work, a multi-objective sustainable network is firstly modeled mathematically to not only curb the direct flow of relief supplies among specific components, but also to operate the reverse flow of waste within the network. Furthermore, in accordance with the Sustainable Development Goals (SDGs), the model emphasizes the energy consumption of critical activities like production and transportation. Additionally, an IoMT configuration is propounded to strengthen the mathematical model with real-time data. metaheuristic optimizers are effective toolkits owing to the NP-hardness of the model. To ensure that the model is compatible and applicable under varying conditions, a suite of tuned metaheuristic optimizers is utilized as well as five scales of test problems. Additionally, the performance of optimizers is examined using a number of recognized performance indicators. The normality of the results is evaluated through statistical tests, namely the Kolmogorov-Smirnov and Shapiro-Wilk tests. Following this assessment, a comprehensive analysis is carried out using the Wilcoxon test and Paired-Samples T Test to compare the results in a pairwise manner, while maintaining a significance level of 0.05. The outcomes derived from these tests reveal the presence of significant disparities among the performance indicators. To ascertain the algorithm with superior performance, an evaluation is conducted using interval plots and the Friedman test, considering each individual performance indicator. The empirical evidence derived from this analysis indicates that the Multi-objective Seagull Optimization Algorithm (MOSOA) exhibited the highest overall mean rank score of 1.93, surpassing other metaheuristic algorithms in terms of performance.

Integrating pre and post-disaster activities for designing an equitable humanitarian relief supply chain

The design of an efficient humanitarian relief supply chain (HRSC) for disaster management depends on the integration of pre- and post-disaster decisions, which reduces the suffering of the victims and saves lives. The use of strategies such as quantity flexibility contracts in the pre-disaster phase and evacuation management in the post-disaster phase significantly increase the efficiency of HRSCs for disaster management. Therefore, in this paper, for the first time, a comprehensive two-stage stochastic mixed-integer linear programming model is presented for integrating the pre- and post-disaster activities for possible disasters such as floods and earthquakes by considering quantity flexibility contract and equitable relief goods distribution. In addition, the proposed model determines the location of warehouses and inventory levels in these warehouses in the pre-disaster phase. It also deals with public donations and budget planning, planning vehicles and helicopters, locating hospitals and shelters, and optimizing the inventory flow between echelons in the post-disaster phase. In the proposed model, the quantity flexibility contract is applied to decrease the inventory level in the pre-disaster phase, and reduce the supply risk in the post-disaster phase. The efficiency and performance of the proposed model are evaluated using the data related to a possible earthquake in Karaj (one of the metropolises of Iran).

Entropy in the “entrepot”: examining the challenges of relief supply chains during COVID-19 pandemic relief item distribution operation-2020 in Uganda

Background: The study focuses on the challenges encountered during the distribution of food and face-mask items during the first COVID-19 lock-down by various relief supply chain actors. Methods: Data were collected from forty (40) relief actors through online (via Zoom and telephones) and face-to-face interviews, between January 2021 to March 2021. Data was coded based on per-determined themes after which it was further processed using Atlas ti. v7.57 to generate patterns. Results: The study established challenges related to needs identification, procurement, warehousing, transportation, handling, beneficiary verification, and last-mile distribution. Additionally, the media and politics coupled with the emergence of new actors and governance issues were part of the challenges identified. Conclusions: The identified challenges were internal and external to the relief supply chain; hence actors could have control over some while others were beyond their control. The findings could inform practitioners and policymakers on what challenges are likely to affect their operations, especially during a pandemic, and design appropriate coping mechanisms.

An integrated operations model for supply of relief items under path disruptions

The integration of relief supply chain operations is critical for the timely supply of relief items to the areas affected by disasters. This work considers a two stage relief supply chain providing relief kit to the areas affected by flood type disaster. Floods often cause path blockages that affect the supply of relief items. A mixed integer linear programming model is formulated for the integrated production and outbound distribution scheduling problem considered and is solved by using a mathematical solver. Since solvers have computational issues in solving realistically sized problems, a Selective Hybrid Genetic Algorithm (SHGA), which performs a selective local search, is proposed. The proposed SHGA produces near optimal solutions in relatively short computation times which is beneficial for quick decision making. A sensitivity analysis is also performed and the path disruption is found to be the most significant input parameter influencing the model.

Evolutionary dynamics of supervision-compliance game on optimal pre-positioning strategies in relief supply chain management

Emergency supply reserves are indispensable material bases in relief supply chain management. However, limited in-kind relief resources stockpiled in government-managed depositories may fail to meet the surging demand following the disaster. This paper develops an optimal pre-positioning strategy for emergency supplies with pre-purchasing contracts between local governments (LGs) and emergency supply manufacturers (ESMs) to properly address demand uncertainty in different disaster scenarios. Physical materials and production capacity are integrated into a holistic and hybrid reserve model to mitigate overstock or stock-out risks. Applying an evolutionary game-theoretic framework, contract enforcement has been extensively analyzed to avoid LGs dereliction of duty and ESMs’ breach of contract. A novel dynamic penalty mechanism is proposed to control the fluctuations in strategy choices and effectively improve ESMs’ compliance without LGs’ excessive inputs on supervision. The numerical simulation results, along with sensitivity analyses on major cost-accounting, demand characteristics, and environmental parameters, show that safety stock is the primary guarantee in most cases, while reactive stock acts as an important supplement for disasters with long-term consequences. The joint reserve policy (except for no action strategy) outperforms the price-only contract on the total reserved quantity of emergency supplies at a lower long-term average cost. The initial state and cost-benefit structures dominate the complex interplay and periodical fluctuations in the supervision-compliance game. The doomed cycle of order, disorder, and reorder in contract performance management can be well managed under the proposed dynamic penalty mechanism, which appears much more efficient and incentive-compatible in promoting both parties to fulfill their obligations.

A bi-objective robust possibilistic cooperative gradual maximal covering model for relief supply chain with uncertainty

The occurrence of natural and artificial disasters due to their unexpected nature requires precise planning and management in the relief supply chain. A major measure in times of crisis is to assist the damaged points. Due to the limitations in the relief process at the time of the accident, relief centers should be opened in appropriate locations that cover the needs of the damaged points in the shortest possible time. Initially, a nonlinear two-level cooperative gradual maximal covering model in relief supply chain is proposed first. The chain includes supply centers, relief, and damaged points under uncertainty of some key parameters. The major goal is to locate the relief centers and determine the allocations and transfer of goods between the two levels. The bi-objective model minimizes the high logistical costs and maximizes damaged points’ coverages with uncertain costs. Different robust possibilistic programming approaches have utilized the given approaches’ performances, and some suitable recommendations are given. The robust possibilistic model provides the best results among all models. The results show that the robust possibilistic programming model outperforms the possibilistic programming model.

Competitive Relief Supply Chain under the Uncertain Conditions

Relief operations and planning to implement them are essential due to the unpredictability of natural disaster occurrences and their concomitant damages. The Crisis and Disaster Management Organization’s responsibility is to execute plans, coordinate, control relief, and rescue operations to reduce the impacts and consequences of these disasters. Thus, this organization should attend to the struck regions’ needs with their maximum power as soon as possible. This study has initially reviewed the latest available literature regarding the humanitarian supply chain to determine the research gap. Accordingly, in this research, a mathematical model with a leader-follower approach for relief delivery in the crisis response phase was designed, which took into account the policies of the country of Iran for the distribution of relief items. The amount of inventory of suppliers was also considered as uncertain. Then, to validate it, a numerical example was solved by the metaheuristic algorithm MOEA/D. The results indicated that the designed model is valid and the selected algorithm to solve it has an acceptable performance. Finally, some effective parameters were selected in the model and the sensitivity of the model was evaluated based on their changes.

An emergency supplies procurement strategy based on a bidirectional option contract

The occurrence of a disaster and its location, type, intensity, scope and duration are highly uncertain, making it hard to accurately estimate the emergency demand. As the main purchasers and managers of emergency supplies, governments face shortage and surplus risks when pre-purchasing and reserving emergency supplies before disasters occur. To address this dilemma, we design an emergency supplies procurement strategy based on a bidirectional option contract (BOC) by considering the system as a relief supply chain. Expected profit functions of the relief supply chain members include the procurement cost, inventory cost and production cost of emergency supplies, the cost and revenue of option trading, the salvage value and the value of demand satisfaction. We derive the purchaser’s optimal procurement portfolio and demonstrate that the BOC enables the coordination of the relief supply chain. We illustrate the superiority of the BOC procurement strategy over the benchmark procurement scenario without the use of the BOC. As an extension, we also compare the BOC with two unilateral option contracts in emergency supplies procurement and summarise the advantage of the BOC. The research extends the application context of the BOC and provides a feasible strategy for governments to procure emergency supplies.

Effective and Efficient Relief Supply Chain Management: A Case Study of Flood Relief-2022 in Sindh

In the backdrop of recent floods in Pakistan, this study focuses to identify the challenges faced in the aid distribution supply chain and envision best practices from Business Supply Chains for use across the relief projects. The argument is that relevant aspects of business supply chain can be applied for operational efficiency of relief supply chain. Using a mixed method approach, seven organizations based in Karachi were selected using purposive sampling method and data was collected using questionnaire having both open and closed ended questions. The quantitative data was analyzed using Microsoft excel and qualitative data was analyzed by thematic analysis. The findings of the study show that all the stakeholders agreed that coordination and collaboration in relief work can increase the effectiveness. The main challenges faced by them were inadequate financial resources, accessing the affected areas, duplication of the relief operation in same areas, as some of the areas got the attention of all relief actors while others got missed at a given time. The research suggests that by adapting CPFR model, Collaborative Planning, Forecasting and Replenishment in the supply chain approach, combined effort and practices can increase the efficiency and effectiveness of relief work.