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A multiperiod household waste collection system for a set of rural islands with dynamic transfer port selection
The design of a household waste collection system must integrate decisions related to planning and control of all related operations, which may...
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Pipeline network design for gathering unconventional oil and gas production using mathematical optimization
The optimal design of gathering networks for the unconventional oil and gas production is a relevant problem, particularly with the shale boom. In...
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Multiperiod optimization model for oilfield production planning: bicriterion optimization and two-stage stochastic programming model
In this work, we present different tools of mathematical modeling that can be used in oil and gas industry to help improve the decision-making for...
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Adjustability in robust linear optimization
We investigate the concept of adjustability—the difference in objective values between two types of dynamic robust optimization formulations: one...
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A Multi-Period Constrained Multi-Objective Evolutionary Algorithm with Orthogonal Learning for Solving the Complex Carbon Neutral Stock Portfolio Optimization Model
Financial market has systemic complexity and uncertainty. For investors, return and risk often coexist. How to rationally allocate funds into...
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A Bayesian approach to data-driven multi-stage stochastic optimization
Aimed at sufficiently utilizing available data and prior distribution information, we introduce a data-driven Bayesian-type approach to solve...
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Preprocessing algorithm and tightening constraints for multiperiod blend scheduling: cost minimization
While a range of models have been proposed for the multiperiod blend scheduling problem (MBSP), solving even medium-size MBSP instances remains...
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Surface facility optimization for combined shale oil and gas development strategies
In the context of a global energy transition, oil and gas will remain an important part of the energy mix, especially in develo** countries. The...
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Risk-Averse Stochastic Programming and Distributionally Robust Optimization Via Operator Splitting
This work deals with a broad class of convex optimization problems under uncertainty. The approach is to pose the original problem as one of finding...
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Stochastic Optimization Methods for the Stochastic Storage Process Control
Many stochastic optimal control problems have analytical solutions up to unknown numerical parameters. We demonstrate this fact with several examples...
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Multiscale stochastic optimization: modeling aspects and scenario generation
Real-world multistage stochastic optimization problems are often characterized by the fact that the decision maker may take actions only at specific...
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The Impact of General Correlation Under Multi-Period Mean-Variance Asset-Liability Portfolio Management
This paper studies the multi-period mean-variance (MV) asset-liability portfolio management problem (MVAL), in which the portfolio is constructed by...
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Multi-Period Telser’s Safety-First Portfolio Selection Problem in a Defined Contribution Pension Plan
This paper investigates a multi-period portfolio optimization problem for a defined contribution pension plan with Telser’s safety-first criterion....
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Globally optimal scheduling of an electrochemical process via data-driven dynamic modeling and wavelet-based adaptive grid refinement
Electrochemical recovery of succinic acid is an electricity intensive process with storable feeds and products, making its flexible operation...
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Discrete-Time Portfolio Optimization under Maximum Drawdown Constraint with Partial Information and Deep Learning Resolution
We study a discrete-time portfolio selection problem with partial information and maximum drawdown constraint. Drift uncertainty in the...
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Multi-Period Portfolio Management and a Simple Method for Calculating the Realized Return with Transaction Costs
In this work the authors provide a detailed analysis of multi-period portfolio transactions with transaction costs under a fixed and finite...
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Markov decision processes with risk-sensitive criteria: an overview
The paper provides an overview of the theory and applications of risk-sensitive Markov decision processes. The term ’risk-sensitive’ refers here to...
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Branch-and-price for a class of nonconvex mixed-integer nonlinear programs
This work attempts to combine the strengths of two major technologies that have matured over the last three decades: global mixed-integer nonlinear...
