Disaster Relief Logistics Research Articles

Development of a Disaster Relief Logistics Model Minimizing the Range of Delivery Time

Development of a Disaster Relief Logistics Model Minimizing the Range of Delivery Time

A Two-Stage Vehicle Routing Algorithm Applied to Disaster Relief Logistics after the 2015 Nepal Earthquake

After the April 2015 Nepal Earthquake, the Himalayan Disaster Relief Volunteer Group distributed supplies to affected areas. We model HDRVG's operations as a vehicle routing problem using Fisher and Jaikumar's two stage method, which allocates locations to vehicles via an integer program and then uses heuristics to route the vehicles. In the allocation stage, we use the assignment problem formulation to assign locations to vehicles. In the routing stage, we implement multiple heuristics for the sake of comparison. Our results illustrate the open nature of the vehicle routing problem and the computational necessity of heuristics.

Disaster relief logistics operation: an insight from Ghana

PurposeCoordinating logistics in the midst of a relief operation is often an overwhelming job that can jeopardise the human life and assets if not done rapidly and practicably. The purpose of this paper is to evaluate the performance of relief logistics in a disaster situation in Ghana with emphasis on the coordination of emergency relief operation and effectiveness of inventory management.Design/methodology/approachA stratified sampling method was employed to a sample of 134 respondents from regional, district and municipal offices in the National Disaster Management Organisation in Ghana using a self-administered questionnaire.FindingsThe findings from this study revealed an effective assessment time but late delivery of relief items. They also revealed issues with respect to resource availability, inventory management and coordination with relief actors which resulted in slow response to affected population.Practical implicationsThe result from this study reveals an ineffective disaster relief response. The practical implications of this issue have been highlighted. In addition, ways to effectively address this issue have been discussed.Originality/valueDrawing insight from previous work and study finding, the paper presents a framework for effective relief logistics operation focussing on all relevant actors in each phase of disaster.

A Multiple-Objective Ant Colony Algorithm for Optimizing Disaster Relief Logistics

A Multiple-Objective Ant Colony Algorithm for Optimizing Disaster Relief Logistics

Fuzzy multi-objective stochastic programming model for disaster relief logistics considering telecommunication infrastructures: a case study

In humanitarian relief logistics, providing a safe place for evacuees, supplying relief commodities and designing a proper telecommunication infrastructure, for fast communications during disaster, are important issues. Therefore, in this paper, we develop a fuzzy scenario-based optimization model concerning location of shelters, relief distribution centers and telecommunication towers. Towards effective management and reliable servicing, telecommunication towers and shelters are considered to constitute integrated facilities (shelter-TTs). Moreover, to enhance efficiency of emergency services during disaster, backup relief distribution centers, and to approach the model to the real world, failure probabilities in the routes and the relief distribution centers are considered. The problem is formulated in a nonlinear and multi-objective model. Nonlinearity is treated by applying heuristic arguments in conjunction with Lp-metrics method. Finally, the developed model for the case study of flood disaster in an urban district in Iran is implemented. The results demonstrate that the proposed model can help make decisions on both the preparation and response phases in humanitarian relief logistics.

An interactive approach for designing a robust disaster relief logistics network with perishable commodities

Pre-positioning of relief commodities in appropriate locations and quantities at a pre-disaster phase assists a disaster relief logistics network in order to efficiently distribute the commodities to demand points; however, a disaster may occur after a long time, and generally perishable commodities (e.g., medical commodities and packed milk) have a fixed lifetime for use. Hence, this paper aims at developing a new integrated model in order to determine the optimum location-allocation and distribution plan, along with the best ordering policy for renewing the stocked perishable commodities at the pre-disaster phase. The uncertain nature of the problem leads to the utilization of a scenario-based robust stochastic approach. The proposed model simultaneously seeks to minimize: (1) the average of the weighted response times and (2) the total operational cost at the pre-disaster phase and the penalty costs of unmet demand and unused commodities at a post-disaster phase. The reservation level Tchebycheff procedure (RLTP) as an interactive approach is also applied to cope with the presented bi-objective model. The significance of the presented model and the efficiency of the RLTP method are then tested via a real case study in Iran.

Drivers and Indicators of Performance in Relief Chain: An Empirical Study

Relief and rehabilitation is an important component of disaster management. Success of this humanitarian intervention is dependent upon a combination of factors; logistics is among the important ones. The purpose of this article is to discuss key drivers of performance while managing disaster relief logistics. This research uses two-stage research designs. The first stage incorporates exploratory research through interviews with experts and focus group discussions. In the second stage, a survey was conducted among those affected by the Kosi floods (2008) in Bihar. A non-random sampling plan was adopted. Results show that there is empirical evidence that the key drivers identified in the present research positively influence the performance of relief operations. This work can also help practitioners and policy makers identify important parameters related to relief logistics. The study was confined to India and only focuses on sudden onset disasters.

Modelling beneficiaries’ choice in disaster relief logistics

This paper introduces the element of beneficiaries’ choice into a location-routing problem for disaster relief logistics suited for decision support systems. Decision makers in humanitarian logistics face the challenge where to establish distribution centers (DCs) for relief goods. For this purpose, two objectives are considered: the impact of the relief operations on the beneficiaries and the efficient use of monetary resources. The proposed multi-objective location-routing model minimizes unserved demand as well as cost for opening DCs and for routing relief goods. It anticipates the choice of beneficiaries to which DC to go (if at all), based on a model adopted from the literature on competitive location analysis. A mathematical programming formulation is presented. For small instances, the Pareto front can be determined exactly using an epsilon constraint method. For solving also realistic instances, an evolutionary algorithm has been implemented and evaluated. The algorithms are tested on real-world instances from Mozambique. The results show that when designing a distribution network, improvements can be achieved by taking the predicted behavior of beneficiaries into account.

A stochastic planning model for humanitarian relief response logistics

During emergencies, decision making to support relief preparedness and response activities are challenging task requiring quick and effective action from responders under uncertainty conditions. This paper proposes a response planning stochastic model for humanitarian transportation operations. The objective of this proposed model is to minimise total transportation duration during emergency situations. This model aims to maximise satisfaction levels through attaining quick response which can help in making decisions on disaster relief logistics.

A stochastic planning model for humanitarian relief response logistics

During emergencies, decision making to support relief preparedness and response activities are challenging task requiring quick and effective action from responders under uncertainty conditions. This paper proposes a response planning stochastic model for humanitarian transportation operations. The objective of this proposed model is to minimise total transportation duration during emergency situations. This model aims to maximise satisfaction levels through attaining quick response which can help in making decisions on disaster relief logistics.

A novel robust chance constrained possibilistic programming model for disaster relief logistics under uncertainty

A novel robust chance constrained possibilistic programming model for disaster relief logistics under uncertainty

Integrated disaster relief logistics: a stepping stone towards viable civil-military networks?

The twenty-first century has seen a significant rise in all forms of disasters and this has resulted in military and humanitarian organisations becoming more frequently engaged in the provision of support to those affected. Achieving an efficient and effective logistic preparation and response is one of the key elements in mitigating the impact of such events, but the establishment of mechanisms to deliver an appropriately integrated civil-military approach remains elusive. Not least because of the high percentage of assistance budgets spent on logistics, this area is considered to represent fertile ground for developing improved processes and understanding. In practice, the demands placed on civilian and military logisticians are broadly similar, as is the solution space. Speaking a common language and using common concepts, it is argued, therefore, that the logistic profession should be in the vanguard of the development of an improved civil-military interface.

Coordinating efficiency and equity in disaster relief logistics via information updates

Coordinating efficiency and equity in disaster relief logistics via information updates

Metaheuristic Algorithm for Solving Biobjective Possibility Planning Model of Location-Allocation in Disaster Relief Logistics

Thousands of victims and millions of affected people are hurt by natural disasters every year. Therefore, it is essential to prepare proper response programs that consider early activities of disaster management. In this paper, a multiobjective model for distribution centers which are located and allocated periodically to the damaged areas in order to distribute relief commodities is offered. The main objectives of this model are minimizing the total costs and maximizing the least rate of the satisfaction in the sense of being fair while distributing the items. The model simultaneously determines the location of relief distribution centers and the allocation of affected areas to relief distribution centers. Furthermore, an efficient solution approach based on genetic algorithm has been developed in order to solve the proposed mathematical model. The results of genetic algorithm are compared with the results provided by simulated annealing algorithm and LINGO software. The computational results show that the proposed genetic algorithm provides relatively good solutions in a reasonable time.

Coordinating efficiency and equity in disaster relief logistics via information updates

This paper addresses a multi-supplier, multi-affected area, multi-relief, and multi-vehicle relief allocation problem in disaster relief logistics. A multi-objective optimisation model based on disaster scenario information updates is proposed in an attempt to coordinate efficiency and equity through timely and appropriate decisions regarding issues such as vehicle routing and relief allocation. An optimal stopping rule is also proposed to determine the optimum period of delay before responding to disaster, because decision making requires accurate disaster information. The main contribution of this paper is solving relief allocation problem in a novel way by correlating operational research with statistical decision making and Bayesian sequential analysis. Finally, a case is presented based on the post-disaster rescue in Eastern China after supertyphoon Saomai to test the applicability and show the potential advantages of the proposed model.

Packaging in developing countries: identifying supply chain needs

PurposeThe purpose of this paper is to explore packaging in developing countries by means of identifying and describing supply chain needs regarding packaging.Design/methodology/approachThe research approach is qualitative and includes an embedded single case study of ambient milk supply chains in developing countries. Data collection is based on the review of internal company documents, semi‐structured interviews with industrial experts and field observations.FindingsThe paper shows that secondary packaging is a vital supply chain component in these countries and that there are extensive interactions between packaging and the supply chain. The findings constitute a list of supply chain needs regarding secondary packaging broken down into categories. Moreover, propositions for managing the supply chain needs and challenges of packaging in developing countries are presented.Research limitations/implicationsIn the supply chains investigated, the focus is on the actors from the filling point at the manufacturer to the point of sale at retail stores in the ambient milk sector. To understand general aspects, the authors suggest further studies to test propositions developed in other contexts.Practical implicationsThe proposed list of packaging supply chain needs and suggested propositions provides insights into the issues and challenges of packaging as a part of designing and planning supply chains in developing countries and, by implication, in humanitarian supply chains that often (but not always) operate in such environments.Originality/valueThis research complements previous research in the areas of packaging and supply chain management by exploring supply chain needs regarding packaging in developing countries. It extends the traditional perspective of humanitarian logistics by linking supply chain thinking in developing countries to long‐term development and disaster relief logistics.

A hierarchical clustering and routing procedure for large scale disaster relief logistics planning

We describe a hierarchical cluster and route procedure (HOGCR) for coordinating vehicle routing in large-scale post-disaster distribution and evacuation activities. The HOGCR is a multi-level clustering algorithm that groups demand nodes into smaller clusters at each planning level, enabling the optimal solution of cluster routing problems. The routing problems are represented as capacitated network flow models that are solved optimally and independently by CPLEX on a parallel computing platform. The HOGCR preserves the consistency among parent and child cluster solutions obtained at consecutive levels. We assess the performance of the algorithm by using large scale scenarios and find satisfactory results.

An auction‐based framework for resource allocation in disaster relief

PurposeThe purpose of this paper is to address the inefficiency problems in procurement operations in disaster relief logistics which are mainly due to the lack of coordination among less organized suppliers and partnerships. Such problems lead to poor responsiveness and hinder timely procurement of required goods.Design/methodology/approachAn auction‐based framework for procurement of goods, which is suitable for a single coordinating platform in disaster relief logistics, is proposed. Integer programming formulations are used in auctioning operations. A simulation model that generates problem instances is used to evaluate and tune system‐level design parameters.FindingsDesign parameters greatly affect the behaviour and responsiveness of the system and the performance of the auction‐based framework in different problem instances. Combinations of those parameters may allow suppliers with limited capacities to become more involved in the bidding process. In addition, the procurement shares of bidders may change substantially with different values of the parameters.Research limitations/implicationsEven though the presented framework is inspired from real‐life applications, it is not implemented in real‐life disaster relief operations. The goodness of fit for the framework would best be evaluated by a real disaster case. In addition, transportation scheduling and vehicle routing considerations and budgeting issues are not considered in the framework.Originality/valueThis paper presents an auction‐based framework for less organized suppliers of goods and their partnerships, such as local humanitarian organizations, private companies, and standby partners. The presented framework offers a background for coordination during disaster relief operations which provides opportunities to act as a set of organized entities. This background also helps those entities coordinate their efforts to enhance the capabilities of local governments and NGOs.

A qualitative study exploring the challenges of humanitarian organisations

PurposeThe purpose of this paper is to identify the underlying issues of humanitarian disaster relief logistics in order to provide an understanding of the challenges facing humanitarian organisations in a wider context.Design/methodology/approachThe paper takes a qualitative approach, adopting a two‐dimensional multi‐strategy research design, culminating in a model of theoretical understanding.FindingsThe results suggest that operational issues encountered in humanitarian logistics are symptomatic of wider issues affecting humanitarian organisations. In understanding this, challenges were identified that, if overcome, could make for more effective relief missions.Research limitations/implicationsIn terms of implications, this paper provides an opportunity for further research, including the testing of the suggested model against an extended sample size which could include senior managers of humanitarian organisations (involved in strategising), and United Nations representative(s).Practical implicationsThe research raises an awareness of the characteristics of humanitarian organisations that may well be acting as barriers to greater effectiveness and efficiency.Originality/valueRather than maintaining an operational focus throughout, the scope and nature of this study provide an insight into humanitarian organisations that allows for a deeper level of understanding to be gained in terms of their characteristics, which broadens the context against which the ensuing discussions/arguments can prevail. The resultant model provides a catalyst for further research and discussion.

A modified particle swarm optimization for disaster relief logistics under uncertain environment

Relief logistics is one of the most important elements of a relief operation. This paper investigates a relief chain design problem where not only demands but also supplies and the cost of procurement and transportation are considered as the uncertain parameters. Furthermore, the model considers uncertainty for the locations where those demands can arise and the possibility that a number of the facility could be partially destroyed by the disaster. The proposed model for this study is formulated as a mixed-integer nonlinear programming to minimize the sum of the expected total cost (which includes costs of location, procurement, transportation, holding, and shortage) and the variance of the total cost. The model simultaneously determines the location of relief distribution centers and the allocation of affected area to relief distribution centers. Furthermore, an efficient solution approach based on particle swarm optimization is developed in order to solve the proposed mathematical model. At last, computational results for several instances of the problem are presented to demonstrate the feasibility and effectiveness of the proposed model and algorithm.