Multi objective optimization for humanitarian logistics operations through the use of mobile technologies
07 Dec 2016-Vol. 6, Iss: 3, pp 399-418
TL;DR: In this paper, a multi-objective optimization model and information system based on mobile technology is presented to support decision making in humanitarian logistics operations, where the trade-off between economic and social (deprivation) costs faced by governmental and nongovernmental organizations (NGOs) involved in humanitarian operations is modeled through a Pareto frontier analysis.
Abstract: Purpose
The purpose of this paper is to present the development and implementation of a multiobjective optimization model and information system based on mobile technology, to support decision making in humanitarian logistics operations.
Design/methodology/approach
The trade-off between economic and social (deprivation) costs faced by governmental and nongovernmental organizations (NGOs) involved in humanitarian logistics operations is modeled through a Pareto frontier analysis, which is obtained from a multiobjective optimization model. Such analysis is supported on an information system based on mobile technology.
Findings
Results show useful managerial insights for decision-makers by considering both economic and social costs associated to humanitarian logistics operations. Such insights include the importance of timely and accurate information shared through mobile technology.
Research limitations/implications
This research presents a multiobjective approach that considers social costs, which are modeled through deprivation functions. The authors suggest that a future nonlinear approach be also considered, since there will be instances where the deprivation cost is a nonlinear function throughout time. Also, the model and information system developed may not be suitable for other humanitarian aid instances, considering the specific characteristics of the events considered on this research.
Practical implications
The inclusion of several types of goods, vehicles, collecting points off the ground, distributions points on the ground, available roads after a disaster took place, as well as volume and weight constraints faced under these scenarios, are considered.
Social implications
Deprivation costs faced by affected population after a disaster took place are considered, which supports decision making in governmental and NGOs involved in humanitarian logistics operations toward welfare of such affected population in developing countries.
Originality/value
A numerical illustration in the Latin American context is presented, the model and information system developed can be used in other developing countries or regions that face similar challenges toward humanitarian logistics operations.
Citations
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30 Apr 2019
TL;DR: In this article, a multi-level facility location problem (FLP) is utilized to find the optimum number of relief centers and refuel stations and their locations to cover a large scale area with minimum and feasible incurred costs and waiting times.
Abstract: Previously use of drones as a relief distribution vehicle was studied in several studies where required number of drones and the best locations for the relief centers were investigated. The maximum travel distance of drones without a need to recharge is limited by their endurance. Recharge stations can be used to extend the coverage area of the drones. The purpose of this paper is to find the best topology for both relief centers and recharge stations to cover a large-scale area with minimum and feasible incurred costs and waiting times.,A multi-level facility location problem (FLP) is utilized to find the optimum number of relief centers and refuel stations and their locations. It is supposed that the demand occurs according to Poisson distribution. The allocation of the demand is based on nearest neighborhood method. A hybrid genetic algorithm is proposed to solve the model. The performance of the algorithm is examined through a case study.,The proposed method delivers increased efficiency and responsiveness of the humanitarian relief system. The coverage area of the drones is extended by refuel stations, total costs of the system are reduced and the time to respond an emergency, which is an important factor in survival rate, is significantly decreased.,This study proposes a multi-level FLP to simultaneously account for recharge stations, relief centers and the number of required drones to cover all the demand for relief in a post-disaster period.
48 citations
TL;DR: In this article, the authors reviewed the recent literature on deprivation costs in humanitarian logistics and its implications from a discussion of key issues, and discussed the key issues in deprivation cost research from the following six perspectives: (1) methodological approaches estimated; (2) the application of deprivation cost; (3) goods or services estimated;(4) differences in estimation; (5) challenges and obstacles; and (6) the gap between the state-of-the-art and the state of the practice of deprivation costs.
Abstract: The field of humanitarian logistics (HL) is attracting an increasing number of scholars. Among the most prominent and promising contributions in this area in recent years was the introduction of the concept of deprivation costs, which is the first attempt to directly quantify human suffering in HL operations. We review the recent literature on deprivation costs in HL, and its implications from a discussion of key issues. This study samples recent literature, applying a four-step systematic review method. The state-of-the-art and the state-of-the-practice of deprivation costs are analyzed. We discuss the key issues in deprivation cost research from the following six perspectives: (1) methodological approaches estimated; (2) the application of deprivation cost; (3) goods or services estimated; (4) differences in estimation; (5) challenges and obstacles; and (6) the gap between the state-of-the-art and the state-of-the-practice. Insights for future research are also discussed.
31 citations
11 Jan 2018
TL;DR: A mathematical model that determines the location of temporary logistics hubs (TLHs) for disaster response and a new method to determine weights of the objectives in a multi-objective optimization problem are developed.
Abstract: Purpose
The purpose of this paper is to develop a mathematical model that determines the location of temporary logistics hubs (TLHs) for disaster response and proposes a new method to determine weights of the objectives in a multi-objective optimization problem. The research is motivated by the importance of TLHs and the complexity that surrounds the determination of their location.
Design/methodology/approach
A multi-period multi-objective model with multi-sourcing is developed to determine the location of the TLHs. A fuzzy factor rating system (FFRS) under the group decision-making (GDM) condition is then proposed to determine the weights of the objectives when multiple decision makers exist.
Findings
The interview with decision makers shows the heterogeneity of decision opinions, thus substantiating the importance of GDM. The optimization results provide useful managerial insights for decision makers by considering the trade-off between two non-commensurable objectives.
Research limitations/implications
In this study, decision makers are considered to be homogeneous, which might not be the case in reality. This study does not consider the stochastic nature of relief demand.
Practical implications
The outcomes of this study are valuable to decision makers for relief distribution planning. The proposed FFRS approach reveals the importance of involving multiple decision makers to enhance sense of ownership of established TLHs.
Originality/value
A mathematical model highlighting the importance of multi-sourcing and short operational horizon of TLHs is developed. A new method is proposed and implemented to determine the weights of the objectives. To the best of the authors’ knowledge, the multi-actor and multi-objective aspects of the TLH location problem have not thus far been considered simultaneously for one particular problem in humanitarian logistics.
29 citations
Cites background or methods from "Multi objective optimization for hu..."
...…of single objective optimization models, many studies have used the multi-objective approach to model different types of problems within humanitarian logistics (Serrato-Garcia et al., 2016; Uster and Dalal, 2016; Jha et al., 2017; Haghi et al., 2017; Tayal and Singh, 2017; Zhou et al., 2017)....
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...Despite the popularity of single objective optimization models, many studies have used the multi-objective approach to model different types of problems within humanitarian logistics (Serrato-Garcia et al., 2016; Uster and Dalal, 2016; Jha et al., 2017; Haghi et al., 2017; Tayal and Singh, 2017; Zhou et al., 2017)....
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16 Jun 2017
TL;DR: In this paper, the authors employ concepts drawn from communication theory to develop a structural model that it is hoped will improve the understanding of the impact of effective communication mechanisms on the performance of humanitarian organizations.
Abstract: Purpose
The purpose of this paper is to employ concepts drawn from communication theory to develop a structural model that it is hoped will improve the understanding of the impact of effective communication mechanisms on the performance of humanitarian organizations.
Design/methodology/approach
The research is based on a case study of a single humanitarian organization. The authors designed a cross-sectional study, collecting data using structured questionnaires and interviews. Structural equation modeling was used to test and estimate the model.
Findings
Estimations show that the proper design of internal manuals and procedure guidelines, coupled with formal strategies to foster stakeholder dialogue in organizations and increase the perceived performance of humanitarian programs.
Practical implications
The paper discusses the importance of designing effective communication strategies that permit humanitarian organizations to use their communication channels properly and improve operations based on lessons learned and the concerns of stakeholders.
Originality/value
This paper builds on the foundations provided by communication theory to develop a model that explains how communication affects performance in humanitarian organizations. The study further builds on a case study to test the theoretical model.
19 citations
TL;DR: The results show that exerting environmental issues in humanitarian logistics does not necessarily increase the relief costs, but can be in contrast with the social aspect, and a minor increase in the budget of the preparedness phase drastically decreases the response costs.
Abstract: As the occurrence of disasters has increased frequently and has resulted in growing concern about their adverse effects on the environment, Sustainable Humanitarian Logistics (SHL) has received great attention recently. SHL aims to reduce disaster damages in an environmentally-friendly manner in the shortest possible time. The terms including ‘environmentally-friendly’ and ‘shortest possible time’ refer to the environmental and social aspects of sustainability. This research proposes a stochastic multi-objective mixed-integer programming model to configure an SHL network during the response phase. Having compared to the research literature, this is the first study that considers economic, social, and environmental aspects of sustainability by incorporating relief cost, deprivation cost, and carbon emissions, respectively. Then, the improved multi-choice goal programming approach is applied to solve the proposed multi-objective model. To indicate the validity of the proposed model, an earthquake that occurred in a region of Kermanshah, Iran, in 2017 is investigated as a real case study. Finally, sensitivity analysis is performed and several managerial and theoretical insights are provided. The results show that exerting environmental issues in humanitarian logistics does not necessarily increase the relief costs, but can be in contrast with the social aspect. Furthermore, a minor increase in the budget of the preparedness phase drastically decreases the response costs.
16 citations
References
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TL;DR: The literature is surveyed to identify potential research directions in disaster operations, discuss relevant issues, and provide a starting point for interested researchers.
1,431 citations
TL;DR: This paper builds on the idea that private sector logistics can and should be applied to improve the performance of disaster logistics but that before embarking on this the private sector needs to be convinced that it can be applied.
Abstract: This paper builds on the idea that private sector logistics can and should be applied to improve the performance of disaster logistics but that before embarking on this the private sector n...
1,398 citations
TL;DR: In this article, a framework for planning and carrying out logistics operations in disaster relief is presented, which distinguishes between actors, phases, and logistical processes of disaster relief, while recognizing the need of humanitarian logistics to learn from business logistics.
Abstract: Purpose – This paper aims to further the understanding of planning and carrying out logistics operations in disaster relief.Design/methodology/approach – Topical literature review of academic and practitioner journals.Findings – Creates a framework distinguishing between actors, phases, and logistical processes of disaster relief. Drawing parallels of humanitarian logistics and business logistics, the paper discovers and describes the unique characteristics of humanitarian logistics while recognizing the need of humanitarian logistics to learn from business logistics.Research limitations/implications – The paper is conceptual in nature; empirical research is needed to support the framework. The framework sets a research agenda for academics.Practical implications – Useful discussion of the unique characteristics of humanitarian logistics. The framework provides practitioners with a tool for planning and carrying out humanitarian logistics operations.Originality/value – No overarching framework for humanit...
1,030 citations
TL;DR: A model that determines the number and locations of distribution centres in a relief network and the amount of relief supplies to be stocked at each distribution centre to meet the needs of people affected by the disasters is developed.
Abstract: In this study, we consider facility location decisions for a humanitarian relief chain responding to quick-onset disasters. In particular, we develop a model that determines the number and locations of distribution centres in a relief network and the amount of relief supplies to be stocked at each distribution centre to meet the needs of people affected by the disasters. Our model, which is a variant of the maximal covering location model, integrates facility location and inventory decisions, considers multiple item types, and captures budgetary constraints and capacity restrictions. We conduct computational experiments to illustrate how the proposed model works on a realistic problem. Results show the effects of pre- and post-disaster relief funding on relief system's performance, specifically on response time and the proportion of demand satisfied. Finally, we discuss the managerial implications of the proposed model.
966 citations
TL;DR: A planning model that is to be integrated into a natural disaster logistics Decision Support System is developed that addresses the dynamic time-dependent transportation problem that needs to be solved repetitively at given time intervals during ongoing aid delivery.
Abstract: Logistics planning in emergency situations involves dispatching commodities (e.g., medical materials and personnel, specialised rescue equipment and rescue teams, food, etc.) to distribution centres in affected areas as soon as possible so that relief operations are accelerated. In this study, a planning model that is to be integrated into a natural disaster logistics Decision Support System is developed. The model addresses the dynamic time-dependent transportation problem that needs to be solved repetitively at given time intervals during ongoing aid delivery. The model regenerates plans incorporating new requests for aid materials, new supplies and transportation means that become available during the current planning time horizon. The plan indicates the optimal mixed pick up and delivery schedules for vehicles within the considered planning time horizon as well as the optimal quantities and types of loads picked up and delivered on these routes. In emergency logistics context, supply is available in limited quantities at the current time period and on specified future dates. Commodity demand is known with certainty at the current date, but can be forecasted for future dates. Unlike commercial environments, vehicles do not have to return to depots, because the next time the plan is re-generated, a node receiving commodities may become a depot or a former depot may have no supplies at all. As a result, there are no closed loop tours, and vehicles wait at their last stop until they receive the next order from the logistics coordination centre. Hence, dispatch orders for vehicles consist of sets of “broken” routes that are generated in response to time-dependent supply/demand. The mathematical model describes a setting that is considerably different than the conventional vehicle routing problem. In fact, the problem is a hybrid that integrates the multi-commodity network flow problem and the vehicle routing problem. In this setting, vehicles are also treated as commodities. The model is readily decomposed into two multi-commodity network flow problems, the first one being linear (for conventional commodities) and the second integer (for vehicle flows). In the solution approach, these sub-models are coupled with relaxed arc capacity constraints using Lagrangean relaxation. The convergence of the proposed algorithm is tested on small test instances as well as on an earthquake scenario of realistic size.
799 citations