scholarly journals Mathematical Optimization Models in the Sugarcane Harvesting Process

2018 ◽  
Author(s):  
Fernando Doriguel ◽  
Carlos Alexandre Costa Crusciol ◽  
Helenice de Oliveira Florentino
Keyword(s):  
Mathematical Optimization ◽  
Optimization Models ◽  
Harvesting Process

scholarly journals Use of Mathematical Optimization Models to Derive Healthy and Safe Fish Intake

2018 ◽  
Vol 148 (2) ◽  
pp. 275-284 ◽  
Author(s):  
Maria Persson ◽  
Sisse Fagt ◽  
Sara M Pires ◽  
Morten Poulsen ◽  
Florent Vieux ◽  
...  
Keyword(s):  
Mathematical Optimization ◽  
Fish Intake ◽  
Optimization Models

A review of mathematical optimization models applied to the sugarcane supply chain

2021 ◽  
Author(s):  
Eduardo dos Santos Teixeira ◽  
Socorro Rangel ◽  
Helenice de O. Florentino ◽  
Silvio Alexandre de Araujo
Keyword(s):  
Supply Chain ◽  
Mathematical Optimization ◽  
Optimization Models

Abstract 185: Optimization of Public Access Defibrillators Compared to Actual Deployment: An In Silico Trial

Circulation ◽  
2018 ◽  
Vol 138 (Suppl_2) ◽  
Author(s):  
Christopher Sun ◽  
Lena Karlsson ◽  
Christian Thorp-Pedersen ◽  
Fredrik Folke ◽  
Timothy C Chan
Keyword(s):  
Real Time ◽  
Confidence Intervals ◽  
In Silico ◽  
Time Horizon ◽  
Mathematical Optimization ◽  
Public Access ◽  
Optimization Models ◽  
Time Interval ◽  
Automated External Defibrillators ◽  
Risk Areas

Introduction: Unguided placement of automated external defibrillators (AEDs) often leads to placements in low risk areas and locations with limited temporal availability. Mathematical optimization may improve AED placements and increase AED use in out-of-hospital cardiac arrests (OHCAs). Aim: To conduct the first in silico public AED location trial to determine whether optimization models (interventions) trained on historical OHCA data will recommend AED locations that significantly improve OHCA coverage on prospective OHCAs, compared to locations of actually deployed AEDs (control). Methods: We identified all public OHCAs of presumed cardiac cause (1994-2016) and already deployed AEDs (2007-2016) in Copenhagen, Denmark. We computed the number of OHCAs that occurred within 100m of a temporally available AED after it was deployed (“OHCA coverage”). We then divided 2007-2016 into 30-day intervals and determined the number of AEDs deployed in each interval. Using previously validated optimization models, we determined an equal number of optimal AED locations in each time interval, either indoor locations with actual availability (intervention #1) or outdoor locations with 24/7 availability (intervention #2). OHCA coverage was calculated for the interventions similarly to the already deployed AEDs. Finally, we repeated the analysis 25 times to evaluate sensitivity and generate confidence intervals, by randomizing the location and time of the OHCAs. Results: A total of 2,149 public OHCAs (744 between 2007-2016) and 1,573 registered AEDs were identified. OHCA coverage of actually deployed AEDs was 22.3% (166 of 744 OHCAs). For optimally located indoor AEDs, mean OHCA coverage was 32.6% (mean: 242.5 OHCAs; 95% CI: 239.7 - 245.3). For optimally located outdoor AEDs, mean OHCA coverage was 43.9% (mean: 326.6 OHCAs; 95% CI: 324.0 - 329.2). Conclusions: Optimizing AED locations in a real-time deployment approach mimicking the time horizon of actual AED deployment in Copenhagen, Denmark results in significantly higher OHCA coverage compared to the actual AEDs deployed. Between the two interventions, optimal locations that are 24/7 available significantly outperform optimal indoor locations with more limited temporal availability.

scholarly journals A Two-Stage Model for Project Optimization in Transportation Infrastructure Management System

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Zhang Chen ◽  
Liyuan Liu ◽  
Li Li ◽  
Hui Li
Keyword(s):  
Management System ◽  
Mathematical Optimization ◽  
Poor Performance ◽  
Optimization Method ◽  
Transportation Infrastructure ◽  
Optimization Models ◽  
Infrastructure Management ◽  
Two Stage ◽  
Maintenance Schedule ◽  
Project Optimization

Mathematical optimization is very important for project decision in the Transportation Infrastructure Management System (TIMS). However, it has not been widely employed in TIMS due to poor performance of conventional optimization models in calculation speed and practical application. Therefore, it is necessary to improve the performance of optimization models. According to the process of decision-making in transportation management, a novel two-stage project optimization model, including budget allocation and project distribution, was proposed in this paper. Moreover, the methods of dynamic programming (DP) and genetic algorithm (GA) were applied to obtain an effective solution. The findings indicate that the new optimization method can provide a satisfactory and reasonable maintenance schedule for transportation infrastructure maintenance agencies whose routine management will benefit from the newly proposed model.

scholarly journals A Systematic Literature Review on Mathematical Models of Humanitarian Logistics

Symmetry ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 11
Author(s):  
Ibrahim M. Hezam ◽  
Moddassir k. Nayeem
Keyword(s):  
Literature Review ◽  
Mathematical Models ◽  
Systematic Literature Review ◽  
Mathematical Optimization ◽  
Humanitarian Logistics ◽  
Optimization Models ◽  
Economic Losses ◽  
Complex Nature ◽  
Deterministic Models ◽  
Relief Distribution

Humanitarian logistics (HL) is considered one of the most significant issues of disaster operations and management. Thus, HL operation should be viable enough to function well under the uncertain and complex nature of the disaster. Many difficulties in pre-and post-disaster phases bring both human and economic losses. Therefore, it is essential to make sure that the HL operations are designed efficiently. In the last two decades, several publications have emphasized efficient HL operations and proposed several mathematical models and algorithms to increase the efficiency of HL operations and motivated the necessity of a systematic literature review. A systematic literature review is deemed pertinent due to its transparent and detailed article searching procedure. In this study, due to the importance of the mathematical optimization model, we reviewed more than one hundred articles published between 2000 and 2020 to investigate the optimization models in the field of HL. We classified the optimization models into three main problems: facility location problems, relief distribution, and mass evacuation where each of the classified areas includes both deterministic and non-deterministic models.

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