Optimizing efficiency of height modeling for extensive forest inventories

2006 ◽  
Vol 36 (9) ◽  
pp. 2259-2269 ◽  
Author(s):  
T M Barrett
Keyword(s):  
Travel Time ◽  
Programming Model ◽  
Sampling Error ◽  
Estimation Error ◽  
Cost Savings ◽  
Data Set ◽  
Potential Measurement ◽  
Forest Inventories ◽  
Alternative Measurement ◽  
Measurement Strategies

Although critical to monitoring forest ecosystems, inventories are expensive. This paper presents a generalizable method for using an integer programming model to examine tradeoffs between cost and estimation error for alternative measurement strategies in forest inventories. The method is applied to an example problem of choosing alternative height-modeling strategies for 1389 plots inventoried by field crews traveling within an 82.5 × 106 ha region of the west coast of North America during one field season. In the first part of the application, nonlinear regional height models were constructed for 38 common species using a development data set of 137 374 measured tree heights, with root mean square error varying from 6.7 to 2.1 m. In the second part of the application, alternative measurement strategies were examined using a minimal cost objective subject to constraints on travel time and estimation error. Reduced travel time for field crews can be a significant portion of the cost savings from modeling tree heights. The optimization model was used to identify a height-modeling strategy that, given assumptions made, resulted in <10% of maximum average plot volume error, >33% of potential measurement cost savings, and small bias for estimates of regional volume and associated sampling error (0.1% and 0.4%, respectively).

Sequential Decision Plans in Monitoring Benthic Macroinvertebrates: Cost Savings, Classification Accuracy, and Development of Plans

1988 ◽  
Vol 45 (2) ◽  
pp. 280-286 ◽  
Author(s):  
John K. Jackson ◽  
Vincent H. Resh
Keyword(s):  
Species Richness ◽  
Species Diversity ◽  
Benthic Macroinvertebrates ◽  
Sampling Error ◽  
Cost Savings ◽  
Spatial And Temporal Variation ◽  
Classification Error ◽  
Sequential Decision ◽  
Data Set ◽  
Acceptable Risks

Sequential decision plans provide a statistical approach that can reduce the number of benthic sample units needed to classify a site as impacted or unimpacted, thus reducing the cost of using benthic macroinvertebrates in water quality assessment programs. These plans require information about unimpacted and impacted conditions, the mathematical distribution of the data, and acceptable risks of classification error. A large benthic data set (n = 55) was used for simulations that created and tested sequential decision plans. Using 10–60% reductions in species richness, mayfly (Cinygmula) population density, and species diversity as definitions of impact in the simulations, the average number of sample units processed for identification of the unimpacted reference site was reduced (compared with fixed sample-size methods that are commonly used) by 50–64% for species richness, 59–79% for density estimates, and 51–55% for species diversity. Unimpacted data sets were initially classified as representing impacted conditions in 0–5% of the cases. If classifications are to be interpreted properly, sampling error and spatial and temporal variation in biological parameters must be considered when sequential decision plans are created.

Socioeconomic patient benefits of a pediatric neurosurgery telemedicine clinic

2020 ◽  
Vol 25 (2) ◽  
pp. 204-208 ◽  
Author(s):  
Kelsey Hayward ◽  
Sabrina H. Han ◽  
Alexander Simko ◽  
Hector E. James ◽  
Philipp R. Aldana
Keyword(s):  
Travel Time ◽  
Cost Savings ◽  
Transportation Cost ◽  
Pediatric Neurosurgery ◽  
University Of Florida ◽  
Remote Location ◽  
Socioeconomic Data ◽  
The University ◽  
Time Away

OBJECTIVEThe objective of this study was to examine the socioeconomic benefits to the patients and families attending a regional pediatric neurosurgery telemedicine clinic (PNTMC).METHODSA PNTMC was organized by the Division of Pediatric Neurosurgery of the University of Florida College of Medicine–Jacksonville based at Wolfson Children’s Hospital and by the Children’s Medical Services (CMS) to service the Southeast Georgia Health District. Monthly clinics are held with the CMS nursing personnel at the remote location. A retrospective review of the clinic population was performed, socioeconomic data were extracted, and cost savings were calculated.RESULTSClinic visits from August 2011 through January 2017 were reviewed. Fifty-five patients were seen in a total of 268 initial and follow-up PNTMC appointments. The average round-trip distance for a family from home to the University of Florida Pediatric Neurosurgery (Jacksonville) clinic location versus the PNTMC remote location was 190 versus 56 miles, respectively. The families saved an average of 2.5 hours of travel time and 134 miles of travel distance per visit. The average transportation cost savings for all visits per family and for all families was $180 and $9711, respectively. The average lost work cost savings for all visits per family and for all families was $43 and $2337, respectively. The combined transportation and work cost savings for all visits totaled $223 per family and $12,048 for all families. Average savings of $0.68/mile and $48.50/visit in utilizing the PNTMC were calculated.CONCLUSIONSManaging pediatric neurosurgery patients and their families via telemedicine is feasible and saves families substantial travel time, travel cost, and time away from work.

scholarly journals Dynamic pricing with demand disaggregation for hotel revenue management

2021 ◽  
Author(s):  
Andrei M. Bandalouski ◽  
Natalja G. Egorova ◽  
Mikhail Y. Kovalyov ◽  
Erwin Pesch ◽  
S. Armagan Tarim
Keyword(s):  
Dynamic Pricing ◽  
Programming Model ◽  
Computer Experiments ◽  
Price Policy ◽  
Linear Constraints ◽  
Economic Consequences ◽  
Elastic Model ◽  
Computationally Efficient ◽  
Data Set ◽  
Dynamic Price

AbstractIn this paper we present a novel approach to the dynamic pricing problem for hotel businesses. It includes disaggregation of the demand into several categories, forecasting, elastic demand simulation, and a mathematical programming model with concave quadratic objective function and linear constraints for dynamic price optimization. The approach is computationally efficient and easy to implement. In computer experiments with a hotel data set, the hotel revenue is increased by about 6% on average in comparison with the actual revenue gained in a past period, where the fixed price policy was employed, subject to an assumption that the demand can deviate from the suggested elastic model. The approach and the developed software can be a useful tool for small hotels recovering from the economic consequences of the COVID-19 pandemic.

scholarly journals A Mathematical Programming Model to Determine Objective Weights for the Interval Extension of TOPSIS

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Hai Shen ◽  
Lingyu Hu ◽  
Kin Keung Lai
Keyword(s):  
Mathematical Programming ◽  
Input Data ◽  
Programming Model ◽  
Multiple Criteria Decision Making ◽  
Decision Makers ◽  
Mathematical Programming Model ◽  
Topsis Method ◽  
Data Set ◽  
Interval Extension ◽  
Interval Valued

Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method has been extended in previous literature to consider the situation with interval input data. However, the weights associated with criteria are still subjectively assigned by decision makers. This paper develops a mathematical programming model to determine objective weights for the implementation of interval extension of TOPSIS. Our method not only takes into account the optimization of interval-valued Multiple Criteria Decision Making (MCDM) problems, but also determines the weights only based upon the data set itself. An illustrative example is performed to compare our results with that of existing literature.

Influence of current injection pattern and electric potential measurement strategies in electrical impedance tomography

2017 ◽  
Vol 58 ◽  
pp. 276-286 ◽  
Author(s):  
Olavo Luppi Silva ◽  
Raul Gonzalez Lima ◽  
Thiago Castro Martins ◽  
Fernando Silva de Moura ◽  
Renato Seiji Tavares ◽  
...  
Keyword(s):  
Electrical Impedance Tomography ◽  
Electric Potential ◽  
Electrical Impedance ◽  
Current Injection ◽  
Impedance Tomography ◽  
Potential Measurement ◽  
Measurement Strategies

Evaluation of Patient Experience from Telemedicine Use for an Anesthesiology Pain Division: Time, Cost, and Patient Satisfaction Analysis (Preprint)

2021 ◽  
Author(s):  
Laleh Jalilian ◽  
Irene Wu ◽  
Jakun Ing ◽  
Xuezhi Dong ◽  
George Pan ◽  
...  
Keyword(s):  
Patient Satisfaction ◽  
Pain Management ◽  
Travel Time ◽  
Medical Center ◽  
Academic Medical Center ◽  
Cost Savings ◽  
Travel Distance ◽  
Patient Cost ◽  
Academic Medical ◽  
Pain Patients

BACKGROUND An increasing number of patients require outpatient and interventional pain management. To help meet the rising demand for anesthesia pain subspecialty care in rural and metropolitan areas, healthcare providers have utilized telemedicine for pain management of both interventional and chronic pain patients. OBJECTIVE This study describes telemedicine implementation for pain management at an academic pain division in a large metropolitan area. The study estimates patient cost savings from telemedicine, before and after the California COVID-19 "Safer at Home" directive, and patient satisfaction with telemedicine for pain management care. METHODS This was a retrospective, observational case series study of telemedicine use in a pain division at an urban academic medical center. From August 2019 to June 2020, we evaluated 1,398 patients and conducted 2,948 video visits for remote pain management care. We utilize publicly available IRS Statistics of Income data to estimate hourly earnings by zip code in order to estimate patient cost savings. We estimate median travel time, travel distance, direct cost of travel, and time-based opportunity savings and report patient satisfaction scores. RESULTS Telemedicine patients avoided an estimated median roundtrip driving distance of 26 miles and a median travel time of 69 minutes during afternoon traffic conditions. Within sample, the median hourly earnings was $28/hr. Patients saved a median of $22 on gas and parking and a total of $52 per telemedicine visit based on estimated hourly earnings and travel time. Patients evaluated serially with telemedicine for medication management saved a median of $156 over three visits. 91% of patients surveyed (n = 313) were satisfied with their telemedicine experience. CONCLUSIONS Telemedicine use for pain management reduced travel distance, travel time, and travel and time-based opportunity costs for pain patients. We achieved the successful implementation of telemedicine across a pain division in an urban academic medical center with high patient satisfaction and patient cost savings.

How Much Do Consumers Value Fuel Economy and Performance? Evidence from Technology Adoption

2021 ◽  
pp. 1-45
Author(s):  
Benjamin Leard ◽  
Joshua Linn ◽  
Yichen Christy Zhou
Keyword(s):  
Fuel Economy ◽  
Cost Savings ◽  
Data Set ◽  
Fuel Savings ◽  
Unique Data ◽  
Consumer Benefit ◽  
Novel Approach ◽  
High Valuation ◽  
And Performance ◽  
Historical Periods

Abstract During historical periods in which US fuel economy standards were unchanging, automakers increased performance but not fuel economy, contrasting with recent periods of tightening standards and rising fuel economy. This paper evaluates the welfare consequences of automakers forgoing performance increases to raise fuel economy as standards have tightened since 2012. Using a unique data set and a novel approach to account for fuel economy and performance endogeneity, we find undervaluation of fuel cost savings and high valuation of performance. Welfare costs of forgone performance approximately equal expected fuel savings benefits, suggesting approximately zero net private consumer benefit from tightened standards.

scholarly journals Stop Plan of Express and Local Train for Regional Rail Transit Line

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Qin Luo ◽  
Yufei Hou ◽  
Wei Li ◽  
Xiongfei Zhang
Keyword(s):  
Energy Consumption ◽  
Travel Time ◽  
Programming Model ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Long Distance ◽  
Passenger Travel ◽  
Urban Rail ◽  
Proposed Model ◽  
Rail Line

The urban rail transit line operating in the express and local train mode can solve the problem of disequilibrium passenger flow and space and meet the rapid arrival demand of long-distance passengers. In this paper, the Logit model is used to analyze the behavior of passengers choosing trains by considering the sensitivity of travel time and travel distance. Then, based on the composition of passenger travel time, an integer programming model for train stop scheme, aimed at minimizing the total passenger travel time, is proposed. Finally, combined with a certain regional rail line in Shenzhen, the plan is solved by genetic algorithm and evaluated through the time benefit, carrying capacity, and energy consumption efficiency. The simulation result shows that although the capacity is reduced by 6 trains, the optimized travel time per person is 10.34 min, and the energy consumption is saved by about 16%, which proves that the proposed model is efficient and feasible.

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