Risk Aversion Based Inexact Stochastic Dynamic Programming Approach for Water Resources Management Planning under Uncertainty
TL;DR: Compared with other optimization methods dealing with uncertainties, the developed DIRSDP method has advantages in addressing uncertainties with complex presentations and reflecting decision makers’ risk-aversion attitudes within its optimization process.
read more
Abstract: In this study, a dual interval robust stochastic dynamic programming (DIRSDP) method is developed for planning water resources management systems under uncertainty. As an extension of the existing interval stochastic dynamic programming (ISDP) method, DIRSDP can deal with two-stage stochastic programming (TSP)-based planning problems associated with dynamic features, input uncertainties, and multistage concerns. Compared with other optimization methods dealing with uncertainties, the developed DIRSDP method has advantages in addressing uncertainties with complex presentations and reflecting decision makers’ risk-aversion attitudes within its optimization process. Parameters in the DIRSDP model can be represented as probability distributions as well as single and/or dual intervals. Decision makers’ risk-aversion attitudes can be reflected through restricting the deviation of the recourse costs to a tolerance level. Water-allocation plans can then be developed based on the analysis of tradeoffs between the system benefit and solution robustness. The developed method is applied to a case of water resources management planning. The solutions are reasonable, indicating applicability of the developed methodology.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
A novel two-stage fuzzy stochastic model for water supply management from a water-energy nexus perspective
TL;DR: A novel two-stage fuzzy stochastic programming approach capable of addressing uncertainties with both possibility and probability distribution is developed for water resources management problems under water-energy nexus to provide managerial insights and suggestions for decision makers to achieve flexible water management.
21
Rural Sustainable Environmental Management
TL;DR: In this paper, the authors focused on the perception of rural sustainable environmental management based on the integration of economic, environmental, and social considerations, and published a special issue, "Rural Sustainable Environmental Management".
6
A Probabilistic Multiperiod Simulation–Optimization Approach for Dynamic Coastal Aquifer Management
TL;DR: In this article, a probabilistic multiperiod combined simulation optimization approach for dynamic groundwater management is proposed to provide sustainable solutions for a coastal aquifer storage and recovery facility in Oman, considering the effect of natural recharge uncertainty.
4
Dynamic Programming Approach in Aggregate Production Planning Model under Uncertainty
Umi Marfuah,Andreas Tri Panudju +1 more
TL;DR: In this article , the authors developed a model under uncertainty with a dynamic programming (DP) approach to meet consumer demand and minimize total costs during the planning period using artificial neural network (ANN) techniques in the demand forecasting process and fuzzy logic (FL) in the DP framework.
Identification of Selected Resource-aware Problems Across Scientific Disciplines and Applications
Pawel Czarnul,Mariusz Matuszek +1 more
TL;DR: The preliminary identification by formulations of resource-aware problems across various disciplines considered in scientific literature of more universal resources considered in many problems, such as financial cost, time, energy, ecological value, security, apart from problem specific resources.
References
Introduction to Stochastic Programming
John R. Birge,Franois Louveaux +1 more
- 27 Jun 2011
TL;DR: This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability to help students develop an intuition on how to model uncertainty into mathematical problems.
6.3K
Robust Optimization of Large-Scale Systems
TL;DR: This paper characterize the desirable properties of a solution to models, when the problem data are described by a set of scenarios for their value, instead of using point estimates, and develops a general model formulation, called robust optimization RO, that explicitly incorporates the conflicting objectives of solution and model robustness.
2K
Environmental policies and productivity growth: Evidence across industries and firms
TL;DR: In this paper, the authors investigated the impact of changes in environmental policy stringency on industry and firm-level productivity growth in a panel of OECD countries, and found that a tightening of environmental policy is associated with a short-term increase in industry level productivity in the most technologically advanced countries.
687
A grey linear programming approach for municipal solid waste management planning under uncertainty
Guohe Huang,Brian W. Baetz,Gilles G. Patry +2 more
- 01 Nov 1992
TL;DR: In this paper, a grey linear programming (GLP) model is introduced to the civil engineering area, which allows uncertainties in the model inputs to be communicated into the optimization process, and thereby solutions reflecting the inherent uncertainties can be derived.
581
An inexact two-stage stochastic programming model for water resources management under uncertainty
Guohe Huang,Daniel P. Loucks +1 more
TL;DR: The ITSP is applied to a hypothetical case study of water resources system operation and results indicate that reasonable solutions have been obtained and the information obtained can provide useful decision support for water managers.
539