Location-Routing for a UAV-Based Recognition System in Humanitarian Logistics: Case Study of Rapid Mapping

2021 ◽  
pp. 197-207
Author(s):  
Paula Saavedra ◽  
Alejandro Pérez Franco ◽  
William J. Guerrero
Keyword(s):  
Recognition System ◽  
Humanitarian Logistics ◽  
Rapid Mapping ◽  
Location Routing

scholarly journals DOLARS, a Distributed On-Line Activity Recognition System by Means of Heterogeneous Sensors in Real-Life Deployments—A Case Study in the Smart Lab of The University of Almería

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 405
Author(s):  
Marcos Lupión ◽  
Javier Medina-Quero ◽  
Juan F. Sanjuan ◽  
Pilar M. Ortigosa
Keyword(s):  
Real Time ◽  
Activity Recognition ◽  
Real Life ◽  
Recognition System ◽  
Machine Learning Algorithms ◽  
Sensor Data ◽  
Heterogeneous Sensors ◽  
On Line ◽  
The University

Activity Recognition (AR) is an active research topic focused on detecting human actions and behaviours in smart environments. In this work, we present the on-line activity recognition platform DOLARS (Distributed On-line Activity Recognition System) where data from heterogeneous sensors are evaluated in real time, including binary, wearable and location sensors. Different descriptors and metrics from the heterogeneous sensor data are integrated in a common feature vector whose extraction is developed by a sliding window approach under real-time conditions. DOLARS provides a distributed architecture where: (i) stages for processing data in AR are deployed in distributed nodes, (ii) temporal cache modules compute metrics which aggregate sensor data for computing feature vectors in an efficient way; (iii) publish-subscribe models are integrated both to spread data from sensors and orchestrate the nodes (communication and replication) for computing AR and (iv) machine learning algorithms are used to classify and recognize the activities. A successful case study of daily activities recognition developed in the Smart Lab of The University of Almería (UAL) is presented in this paper. Results present an encouraging performance in recognition of sequences of activities and show the need for distributed architectures to achieve real time recognition.

A bi-level mathematical model for logistic management considering the evolutionary game with environmental feedbacks

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Peiman Ghasemi ◽  
Fariba Goodarzian ◽  
Angappa Gunasekaran ◽  
Ajith Abraham
Keyword(s):  
Mathematical Model ◽  
Lagrangian Relaxation ◽  
Evolutionary Games ◽  
Relaxation Method ◽  
Objective Functions ◽  
Content Type ◽  
Medical Centers ◽  
Location Routing ◽  
Proposed Model

PurposeThis paper proposed a bi-level mathematical model for location, routing and allocation of medical centers to distribution depots during the COVID-19 pandemic outbreak. The developed model has two players including interdictor (COVID-19) and fortifier (government). Accordingly, the aim of the first player (COVID-19) is to maximize system costs and causing further damage to the system. The goal of the second player (government) is to minimize the costs of location, routing and allocation due to budget limitations.Design/methodology/approachThe approach of evolutionary games with environmental feedbacks was used to develop the proposed model. Moreover, the game continues until the desired demand is satisfied. The Lagrangian relaxation method was applied to solve the proposed model.FindingsEmpirical results illustrate that with increasing demand, the values of the objective functions of the interdictor and fortifier models have increased. Also, with the raising fixed cost of the established depot, the values of the objective functions of the interdictor and fortifier models have raised. In this regard, the number of established depots in the second scenario (COVID-19 wave) is more than the first scenario (normal COVID-19 conditions).Research limitations/implicationsThe results of the current research can be useful for hospitals, governments, Disaster Relief Organization, Red Crescent, the Ministry of Health, etc. One of the limitations of the research is the lack of access to accurate information about transportation costs. Moreover, in this study, only the information of drivers and experts about transportation costs has been considered. In order to implement the presented solution approach for the real case study, high RAM and CPU hardware facilities and software facilities are required, which are the limitations of the proposed paper.Originality/valueThe main contributions of the current research are considering evolutionary games with environmental feedbacks during the COVID-19 pandemic outbreak and location, routing and allocation of the medical centers to the distribution depots during the COVID-19 outbreak. A real case study is illustrated, where the Lagrangian relaxation method is employed to solve the problem.

scholarly journals Location Routing Problem with Consideration of CO2 Emissions Cost: A Case Study

2020 ◽  
Vol 21 (2) ◽  
pp. 225-234
Author(s):  
Ananda Noor Sholichah ◽  
Y Yuniaristanto ◽  
I Wayan Suletra
Keyword(s):  
Co2 Emissions ◽  
Time Windows ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
Study Results

Location and routing are the main critical problems investigated in a logistic. Location-Routing Problem (LRP) involves determining the location of facilities and vehicle routes to supply customer's demands. Determination of depots as distribution centers is one of the problems in LRP.  In LRP, carbon emissions need to be considered because these problems cause global warming and climate change. In this paper, a new mathematical model for LRP considering CO2 emissions minimization is proposed. This study developed a new  Mixed Integer Linear Programming (MILP)  model for LRP with time windows and considered the environmental impacts.  Finally, a case study was conducted in the province of Central Java, Indonesia. In this case study, there are three depot candidates. The study results indicated that using this method in existing conditions and constraints provides a more optimal solution than the company's actual route. A sensitivity analysis was also carried out in this case study.

Supply chain agility in humanitarian protracted operations

2016 ◽  
Vol 6 (2) ◽  
pp. 173-201 ◽  
Author(s):  
Cécile L'Hermitte ◽  
Peter Tatham ◽  
Ben Brooks ◽  
Marcus Bowles
Keyword(s):  
Supply Chain ◽  
Humanitarian Logistics ◽  
Future Research ◽  
Short Term ◽  
Content Type ◽  
Emergency Operations ◽  
Supply Chain Agility ◽  
Agile Practices ◽  
Basic Features

Purpose – The purpose of this paper is to extend the concept of agility in humanitarian logistics beyond emergency operations. Since the humanitarian logistics literature focuses primarily on emergencies and sees longer term and regular operations as being conducted in relatively stable and predictable environments, agile practices are usually not associated with humanitarian protracted operations. Therefore, this paper explores the logistics and supply chain environment in such operations in order to identify their basic features and determine if agility is an important requirement. Design/methodology/approach – Using a case study of the United Nations World Food Programme, the authors collected and analysed qualitative and quantitative data on the characteristics of protracted operations, the risks and uncertainties most frequently encountered, their impact, and the ways that field logisticians manage contingencies. Findings – The research demonstrates that unpredictability and disruptions exist in protracted operations. Therefore, short-term operational adjustments and agile practices are needed in order to support the continuity of humanitarian deliveries. Research limitations/implications – Future research should focus on a wider range of humanitarian organisations and move from a descriptive to a prescriptive approach in order to inform practice. Notwithstanding these limitations, the study highlights the need for academics to broaden the scope of their research beyond emergencies and to address the specific needs of humanitarian organisations involved in longer term operations. Originality/value – This paper is the first empirical research focusing exclusively on the logistics features of humanitarian protracted operations. It provides a more concrete and complete understanding of these operations.

Speaker Recognition With Normal and Telephonic Assamese Speech Using I-Vector and Learning-Based Classifier

2017 ◽  
pp. 256-280
Author(s):  
Mridusmita Sharma ◽  
Rituraj Kaushik ◽  
Kandarpa Kumar Sarma
Keyword(s):  
Neural Network ◽  
Speaker Recognition ◽  
Recognition Rate ◽  
Recognition System ◽  
Feed Forward Neural Network ◽  
Individual Behaviour ◽  
Behavioural Characteristics ◽  
Regional Languages ◽  
Optimal Feature

Speaker recognition is the task of identifying a person by his/her unique identification features or behavioural characteristics that are included in the speech uttered by the person. Speaker recognition deals with the identity of the speaker. It is a biometric modality which uses the features of the speaker that is influenced by one's individual behaviour as well as the characteristics of the vocal cord. The issue becomes more complex when regional languages are considered. Here, the authors report the design of a speaker recognition system using normal and telephonic Assamese speech for their case study. In their work, the authors have implemented i-vectors as features to generate an optimal feature set and have used the Feed Forward Neural Network for the recognition purpose which gives a fairly high recognition rate.

Designing Valid Humanitarian Logistics Scenario Sets

2021 ◽  
pp. 452-469
Author(s):  
Jorge Vargas-Florez ◽  
Matthieu Lauras ◽  
Tina Comes
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Inventory Management ◽  
Support Systems ◽  
Humanitarian Logistics ◽  
The Real ◽  
Quantitative Models ◽  
Location Routing ◽  
Concrete Application ◽  
Case Based

Literature about humanitarian logistics (HL) has developed a lot of innovative decision support systems during the last decades to support decisions such as location, routing, supply, or inventory management. Most of those contributions are based on quantitative models but, generally, are not used by practitioners who are not confident with. This can be explained by the fact that scenarios and datasets used to design and validate those HL models are often too simple compared to the real situations. In this chapter, a scenario-based approach based on a five-step methodology has been developed to bridge this gap by designing a set of valid scenarios able to assess disaster needs in regions subject to recurrent disasters. The contribution, usable by both scholars and practitioners, demonstrates that defining such valid scenario sets is possible for recurrent disasters. Finally, the proposal is validated on a concrete application case based on Peruvian recurrent flood and earthquake disasters.

scholarly journals Location Decision Making and Transportation Route Planning Considering Fuel Consumption

2019 ◽  
Vol 5 (2) ◽  
pp. 27 ◽  
Author(s):  
Chalermchat Theeraviriya ◽  
Rapeepan Pitakaso ◽  
Kittima Sillapasa ◽  
Sasitorn Kaewman
Keyword(s):  
Fuel Consumption ◽  
Palm Oil ◽  
Processing Time ◽  
Computational Study ◽  
Exact Method ◽  
Neighborhood Search ◽  
Fixed Cost ◽  
Location Routing ◽  
Consumption Cost

This study presents the Location Routing Problem (LRP) for which we have created a model for the integration of locating facilities and vehicle routing decisions to solve the problem. The case study is the Palm Oil Collection Center, which is also important for the supply chain system. A mathematical model was made to minimize the total cost of a facility-opening cost, fixed cost of vehicle uses and fuel consumption cost. The fuel consumption cost relies on the distance and road conditions, in case of poor physical condition of a road, and its width, which can be affected the speed of the vehicle as well as the used fuel. Thus, we propose an Adaptive Large Neighborhood Search (ALNS) based on heuristic for solving the LRP. The ALNS method was tested with three datasets of samples divided into small, medium and large problems. Then, the results were compared with the results from the exact method by the Lingo program. The computational study indicated that the ALNS algorithm was competitive to the results of the Lingo for all instance sizes. Moreover, the ALNS was more effective than the exact method; approximately 99% in terms of processing time. We extended this approach to solve the case study, which was considered to be the largest problem, and the ALNS algorithm was efficient with acceptable solutions and short processing time. Therefore, the proposed method provided an effective solution to manage location routing decision of the palm oil collection center.

scholarly journals Relief Demand Calculation in Humanitarian Logistics Using Material Classification

2020 ◽  
Vol 17 (2) ◽  
pp. 582
Author(s):  
Jianfang Shao ◽  
Changyong Liang ◽  
Xihui Wang ◽  
Xiang Wang ◽  
Liang Liang
Keyword(s):  
Disaster Response ◽  
Demand Forecasting ◽  
Humanitarian Logistics ◽  
New Method ◽  
On Demand ◽  
Material Classification ◽  
Response Practice ◽  
Different Types ◽  
General Method

Demand calculation, which is the base of most logistics decisions and activities, is a critical work in humanitarian logistics (HL). However, previous studies on demand calculation in HL mainly focus on demand forecasting methodology, with many neglecting the checklist of critical supplies and practice background. This work proposes a new method for relief demand calculation by dividing the process into two parts: supply classification and demand calculation. A general method for classifying relief supplies and clarifying the checklist of relief items for multi-disaster and multiple natural scenarios is given in detail, followed by the procedure of demand calculation for each relief material. The authors present a case study to validate the feasibility and effectiveness of the proposed method based on the disaster response practice in China. Detailed lists of relief demand for different types and severities of disaster are provided.

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