Sensitivity Analysis of Regional Planning Models

This paper shows the equivalence of entropy-maximization models to geometric programs. As a result we derive a dual geometric program which consists of the minimization of an unconstrained convex function. We develop the necessary duality equivalencies between the two dual programs and show the computational attractiveness of our approach. We also develop some characterizations of the optimal solution of the entropy model which have important implications with regard to postoptimal or sensitivity analysis.

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Sensitivity Analysis in Markov Decision Processes with Uncertain Reward Parameters

Journal of Applied Probability ◽

10.1017/s002190020000855x ◽

2011 ◽

Vol 48 (04) ◽

pp. 954-967 ◽

Cited By ~ 1

Author(s):

Chin Hon Tan ◽

Joseph C. Hartman

Keyword(s):

Sensitivity Analysis ◽

Markov Decision Processes ◽

Lot Sizing ◽

Optimal Solution ◽

Decision Processes ◽

Model Parameters ◽

Sequential Decision ◽

Estimation Errors ◽

Bellman Equations ◽

Markov Decision

Sequential decision problems can often be modeled as Markov decision processes. Classical solution approaches assume that the parameters of the model are known. However, model parameters are usually estimated and uncertain in practice. As a result, managers are often interested in how estimation errors affect the optimal solution. In this paper we illustrate how sensitivity analysis can be performed directly for a Markov decision process with uncertain reward parameters using the Bellman equations. In particular, we consider problems involving (i) a single stationary parameter, (ii) multiple stationary parameters, and (iii) multiple nonstationary parameters. We illustrate the applicability of this work through a capacitated stochastic lot-sizing problem.

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Sensitivity Analysis in Markov Decision Processes with Uncertain Reward Parameters

Journal of Applied Probability ◽

10.1239/jap/1324046012 ◽

2011 ◽

Vol 48 (4) ◽

pp. 954-967 ◽

Cited By ~ 7

Author(s):

Chin Hon Tan ◽

Joseph C. Hartman

Keyword(s):

Sensitivity Analysis ◽

Markov Decision Processes ◽

Lot Sizing ◽

Optimal Solution ◽

Decision Processes ◽

Model Parameters ◽

Sequential Decision ◽

Estimation Errors ◽

Bellman Equations ◽

Markov Decision

Sequential decision problems can often be modeled as Markov decision processes. Classical solution approaches assume that the parameters of the model are known. However, model parameters are usually estimated and uncertain in practice. As a result, managers are often interested in how estimation errors affect the optimal solution. In this paper we illustrate how sensitivity analysis can be performed directly for a Markov decision process with uncertain reward parameters using the Bellman equations. In particular, we consider problems involving (i) a single stationary parameter, (ii) multiple stationary parameters, and (iii) multiple nonstationary parameters. We illustrate the applicability of this work through a capacitated stochastic lot-sizing problem.

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Entropy based transportation model: A geometric programming approach

Yugoslav journal of operations research ◽

10.2298/yjor0701043s ◽

2007 ◽

Vol 17 (1) ◽

pp. 43-54 ◽

Cited By ~ 1

Author(s):

Bablu Samanta ◽

Kumar Majumder

Keyword(s):

Regional Planning ◽

Geometric Programming ◽

Good Deal ◽

Programming Approach ◽

Transportation Model ◽

Entropy Model ◽

Entropy Maximization ◽

Urban And Regional Planning ◽

Mathematical Programs ◽

Geometric Programs

The entropy model has attached a good deal of attention in transportation analysis, urban and regional planning as well as in other areas. This paper shows the equivalence of entropy maximization models to geometric programs. To provide a better understanding of this entropy based transportation model they are analyzed by geometric programming. Dual mathematical programs and algorithms are also obtained and are supported by an illustrative example. .

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Aplikasi Metode Hungarian Dalam Optimalisasi Waktu Penugasan Karyawan dan Keuntungan Produksi Home Industry

Talenta Conference Series Science and Technology (ST) ◽

10.32734/st.v2i2.470 ◽

2019 ◽

Vol 2 (2) ◽

Author(s):

Empya Charlie ◽

Siti Rusdiana ◽

Rini Oktavia

Keyword(s):

Sensitivity Analysis ◽

Optimal Solution ◽

Optimal Scheduling ◽

Total Work ◽

Work Time ◽

Hungarian Method ◽

Total Work Time

Penelitian ini bertujuan untuk mengoptimalkan penjadwalan karyawan di CV. Karya Indah Bordir dalam melakukan tugas-tugas tertentu menggunakan metode Hungaria, serta menganalisis sensitivitas solusi optimal jika ada pengurangan waktu karyawan untuk menyelesaikan tugas-tugas. Metode Hongaria diterapkan pada proses bordir yang melibatkan 11 karyawan dan 10 tugas. Hasil penjadwalan yang optimal meminimalkan waktu produksi bordir perusahaan. Hasil penjadwalan optimal yang ditemukan adalah: karyawan 1 mengerjakan tas Mambo, karyawan 2 mengerjakan tas Elli, karyawan 3 mengerjakan tas Lonjong, karyawan 4 mengerjakan tas Tampang bunga, karyawan 6 mengerjakan tas Ransel, karyawan 7 mengerjakan tas Tima, karyawan 8 mengerjakan tas Keong, karyawan 9 mengerjakan tas Alexa, karyawan 10 mengerjakan tas Luna, dan karyawan 11 mengerjakan tas Mikha, dengan total waktu kerja adalah 13,7 jam. Setelah metode Hongaria diterapkan, CV. Karya Indah Bordir mendapat peningkatan pendapatan sebanyak 9,09%. Analisis sensitivitas dilakukan dengan mengurangi waktu karyawan dalam menyulam tas. Hasil analisis sensitivitas adalah beberapa batasan untuk variabel basis dan non basis untuk mempertahankan solusi optimal. This research has a purpose to optimize the scheduling of employees in CV. Karya Indah Bordir in doing certain tasks using Hungarian method, as well as analyzing the sensitivity of the optimal solution if there is a reduction on the employees time to finish the tasks. The Hungarian method was applied on the embroidery process involving 11 employees and 10 tasks. The optimal scheduling result minimize the time of the embroidery production of the company. The optimal scheduling result found is: employee 1 does the Mambo bag, employee 2 does the Elli bag, employee 3 does the Lonjong bag, employee 4 does the Tampang bunga bag, employee 6 does the Ransel, employee 7 does the Tima bag, employee 8 does the Keong bag, employee 9 does the Alexa bag, employees 10 does the Luna bag, and employee 11 does the Mikha bag, with the total work time is 13,7 hours. After the Hungarian method was applied, CV. Karya Indah Bordir got the increasing revenue as much as 9,09 %. The sensitivity analysis was conducted by reducing the time of the employees take in embroidery the bags. The results of the sensitivity analysis are some boundaries for basis and non basis variables to maintain the optimal solution.

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'Planning Economic Integration7, by L.B.M. Mennes, Rotterdam University Press, 1973.

The Pakistan Development Review ◽

10.30541/v12i4pp.438-439 ◽

1973 ◽

Vol 12 (4) ◽

pp. 438-439

Author(s):

G. M. Radhul

Keyword(s):

Economic Integration ◽

Point Of View ◽

Planning Model ◽

Integration Policy ◽

Medium Term ◽

Future Production ◽

Planning Models ◽

Partici Pant ◽

The Impact ◽

Integration Area

The book under review deals with economic integration among deve¬loping countries from the point of view of planning. The author believes that it is useful to approach economic integration from a planning point of view and to develop planning models for it, because the theory of economic integration relevant for developing countries should be directed towards the impact of integration on future investments and future production. The type of models used in the book are the multisector linear programming models and the method of analysis is essentially a comparison of two situations; one with economic integration and the other without. For each prospective partici¬pant a medium term planning model is drawn up taking account of its economic situation in some base year. The results of these single country planning models are analysed and compared to those of a similar planning model for the integration area as a whole. The consequences of the integration policy are then evaluated.

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A Sensitivity Analysis of the SPACSYS Model

Agriculture ◽

10.3390/agriculture11070624 ◽

2021 ◽

Vol 11 (7) ◽

pp. 624

Author(s):

Yan Shan ◽

Mingbin Huang ◽

Paul Harris ◽

Lianhai Wu

Keyword(s):

Sensitivity Analysis ◽

Wheat Yield ◽

Climatic Conditions ◽

Water Dynamics ◽

Ecological Modelling ◽

Soil Conditions ◽

Model Parameters ◽

Nutrient Inputs ◽

Nutrient Pool ◽

Wheat Field

A sensitivity analysis is critical for determining the relative importance of model parameters to their influence on the simulated outputs from a process-based model. In this study, a sensitivity analysis for the SPACSYS model, first published in Ecological Modelling (Wu, et al., 2007), was conducted with respect to changes in 61 input parameters and their influence on 27 output variables. Parameter sensitivity was conducted in a ‘one at a time’ manner and objectively assessed through a single statistical diagnostic (normalized root mean square deviation) which ranked parameters according to their influence of each output variable in turn. A winter wheat field experiment provided the case study data. Two sets of weather elements to represent different climatic conditions and four different soil types were specified, where results indicated little influence on these specifications for the identification of the most sensitive parameters. Soil conditions and management were found to affect the ranking of parameter sensitivities more strongly than weather conditions for the selected outputs. Parameters related to drainage were strongly influential for simulations of soil water dynamics, yield and biomass of wheat, runoff, and leaching from soil during individual and consecutive growing years. Wheat yield and biomass simulations were sensitive to the ‘ammonium immobilised fraction’ parameter that related to soil mineralization and immobilisation. Simulations of CO2 release from the soil and soil nutrient pool changes were most sensitive to external nutrient inputs and the process of denitrification, mineralization, and decomposition. This study provides important evidence of which SPACSYS parameters require the most care in their specification. Moving forward, this evidence can help direct efficient sampling and lab analyses for increased accuracy of such parameters. Results provide a useful reference for model users on which parameters are most influential for different simulation goals, which in turn provides better informed decision making for farmers and government policy alike.

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Global Sensitivity Analysis of a Homogenized Constrained Mixture Model of Arterial Growth and Remodeling

Journal of Elasticity ◽

10.1007/s10659-021-09833-9 ◽

2021 ◽

Author(s):

Sebastian Brandstaeter ◽

Sebastian L. Fuchs ◽

Jonas Biehler ◽

Roland C. Aydin ◽

Wolfgang A. Wall ◽

...

Keyword(s):

Sensitivity Analysis ◽

Global Sensitivity Analysis ◽

Model Parameters ◽

Computational Studies ◽

Growth And Remodeling ◽

Global Sensitivity ◽

Output Variability ◽

Constrained Mixture ◽

The One ◽

Influential Parameters

AbstractGrowth and remodeling in arterial tissue have attracted considerable attention over the last decade. Mathematical models have been proposed, and computational studies with these have helped to understand the role of the different model parameters. So far it remains, however, poorly understood how much of the model output variability can be attributed to the individual input parameters and their interactions. To clarify this, we propose herein a global sensitivity analysis, based on Sobol indices, for a homogenized constrained mixture model of aortic growth and remodeling. In two representative examples, we found that 54–80% of the long term output variability resulted from only three model parameters. In our study, the two most influential parameters were the one characterizing the ability of the tissue to increase collagen production under increased stress and the one characterizing the collagen half-life time. The third most influential parameter was the one characterizing the strain-stiffening of collagen under large deformation. Our results suggest that in future computational studies it may - at least in scenarios similar to the ones studied herein - suffice to use population average values for the other parameters. Moreover, our results suggest that developing methods to measure the said three most influential parameters may be an important step towards reliable patient-specific predictions of the enlargement of abdominal aortic aneurysms in clinical practice.

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Gaussian Processes Proxy Model with Latent Variable Models and Variogram-Based Sensitivity Analysis for Assisted History Matching

Energies ◽

10.3390/en13174290 ◽

2020 ◽

Vol 13 (17) ◽

pp. 4290

Author(s):

Dongmei Zhang ◽

Yuyang Zhang ◽

Bohou Jiang ◽

Xinwei Jiang ◽

Zhijiang Kang

Keyword(s):

Sensitivity Analysis ◽

Gaussian Processes ◽

Latent Variable ◽

History Matching ◽

Latent Variable Models ◽

High Dimensional ◽

Model Parameters ◽

Variable Model ◽

Assisted History Matching ◽

Proxy Models

Reservoir history matching is a well-known inverse problem for production prediction where enormous uncertain reservoir parameters of a reservoir numerical model are optimized by minimizing the misfit between the simulated and history production data. Gaussian Process (GP) has shown promising performance for assisted history matching due to the efficient nonparametric and nonlinear model with few model parameters to be tuned automatically. Recently introduced Gaussian Processes proxy models and Variogram Analysis of Response Surface-based sensitivity analysis (GP-VARS) uses forward and inverse Gaussian Processes (GP) based proxy models with the VARS-based sensitivity analysis to optimize the high-dimensional reservoir parameters. However, the inverse GP solution (GPIS) in GP-VARS are unsatisfactory especially for enormous reservoir parameters where the mapping from low-dimensional misfits to high-dimensional uncertain reservoir parameters could be poorly modeled by GP. To improve the performance of GP-VARS, in this paper we propose the Gaussian Processes proxy models with Latent Variable Models and VARS-based sensitivity analysis (GPLVM-VARS) where Gaussian Processes Latent Variable Model (GPLVM)-based inverse solution (GPLVMIS) instead of GP-based GPIS is provided with the inputs and outputs of GPIS reversed. The experimental results demonstrate the effectiveness of the proposed GPLVM-VARS in terms of accuracy and complexity. The source code of the proposed GPLVM-VARS is available at https://github.com/XinweiJiang/GPLVM-VARS.

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Cost-effectiveness of TAS-102 plus bevacizumab versus TAS-102 monotherapy in patients with metastatic colorectal cancer

BMC Gastroenterology ◽

10.1186/s12876-021-01771-z ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Kiyoaki Sugiura ◽

Yuki Seo ◽

Takayuki Takahashi ◽

Hideyuki Tokura ◽

Yasuhiro Ito ◽

...

Keyword(s):

Colorectal Cancer ◽

Health Care ◽

Sensitivity Analysis ◽

Cost Effectiveness ◽

Combination Therapy ◽

Metastatic Colorectal Cancer ◽

Cost Effective ◽

Model Parameters ◽

Combination Regimen ◽

The Cost

Abstract Background TAS-102 plus bevacizumab is an anticipated combination regimen for patients who have metastatic colorectal cancer. However, evidence supporting its use for this indication is limited. We compared the cost-effectiveness of TAS-102 plus bevacizumab combination therapy with TAS-102 monotherapy for patients with chemorefractory metastatic colorectal cancer. Method Markov decision modeling using treatment costs, disease-free survival, and overall survival was performed to examine the cost-effectiveness of TAS-102 plus bevacizumab combination therapy and TAS-102 monotherapy. The Japanese health care payer’s perspective was adopted. The outcomes were modeled on the basis of published literature. The incremental cost-effectiveness ratio (ICER) between the two treatment regimens was the primary outcome. Sensitivity analysis was performed and the effect of uncertainty on the model parameters were investigated. Results TAS-102 plus bevacizumab had an ICER of $21,534 per quality-adjusted life-year (QALY) gained compared with TAS-102 monotherapy. Sensitivity analysis demonstrated that TAS-102 monotherapy was more cost-effective than TAS-102 and bevacizumab combination therapy at a willingness-to-pay of under $50,000 per QALY gained. Conclusions TAS-102 and bevacizumab combination therapy is a cost-effective option for patients who have metastatic colorectal cancer in the Japanese health care system.

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