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Displaying results 1 to 21 of 21.

  1. Optimum turn-restricted paths, nested compatibility, and optimum convex polygons
    Author: Queyranne, Maurice; Wolsey, Laurence A.
    Published: [2016]
    Publisher:  Centre for Operations Research and Econometrics, Louvain-la-Neuve

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    Language: English
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    hdl: 2078.1/174579
    Series: CORE discussion papers ; 2016, 20
    Subjects: shortest paths; acyclic networks; turn restrictions; convex polygons; convex subsets; extended formulation; dynamic programming
    Scope: 1 Online-Ressource (circa 24 Seiten), Illustrationen
  2. Sequential testing of n-outof-n systems
    precedence theorems and exact methods
    Author: Rostami, Salim; Creemers, Stefan; Wei, Wenchao; Leus, Roel
    Published: [2018]
    Publisher:  KU Leuven, Faculty of Economics and Business, Leuven, België

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    Format: Online
    Series: KBI ; KBI_18, 06
    Subjects: sequencing; system testing; precedence theorems; dynamic programming; branch-and-price
    Scope: 1 Online-Ressource (circa 26 Seiten), Illustrationen
  3. Fast Upper-Envelope Scan for Discrete-Continuous Dynamic Programming
    Author: Dobrescu, Loretti Isabella; Shanker, Akshay
    Published: 2022
    Publisher:  SSRN, [S.l.]

    We introduce a fast upper-envelope scan (FUES) method to compute solutions for dynamic programming problems with continuous and discrete choices. The FUES method builds on the standard endogenous grid method (EGM). Standard EGM applied to problems... more

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    We introduce a fast upper-envelope scan (FUES) method to compute solutions for dynamic programming problems with continuous and discrete choices. The FUES method builds on the standard endogenous grid method (EGM). Standard EGM applied to problems with continuous and discrete choices does not by itself generate the optimal solution since the first order conditions used to generate the endogenous grid are necessary but not sufficient. FUES sequentially checks EGM candidate solution points and eliminates points not on the upper-envelope of the value correspondence by only allowing discontinuities in the policy function at non-concave sections of the value correspondence. FUES is computationally efficient, involves minimal coding time or analysis on the researcher side and does not require monotonicity assumptions on the problem. We also show that if the EGM grid size is sufficiently large, FUES is guaranteed to recover the optimal solution without error. FUES can be applied to many standard economic models, involving housing frictions, firm investment frictions, portfolio allocation or labor market participation decisions

     
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    Series: UNSW Business School Research Paper
    Subjects: dynamic programming; computational methods; non-convex optimization; Euler equations
    Other subjects: Array
    Scope: 1 Online-Ressource (27 p)
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    Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments August 4, 2022 erstellt
  4. The art of temporal approximation
    an investigation into numerical solutions to discrete & continuous-time problems in economics
    Author: Eslami, Keyvan; Phelan, Thomas M.
    Published: [2023]
    Publisher:  Federal Reserve Bank of Cleveland, [Cleveland, OH]

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    Series: Federal Reserve Bank of Cleveland working paper series ; no. 23, 10 (May 2023)
    Subjects: Markov chain approximation; dynamic programming; numerical methods; income fluctuation problems
    Scope: 1 Online-Ressource (circa 47 Seiten), Illustrationen
  5. Disequilibrium play in tennis
    Author: Anderson, Axel; Rosen, Jeremy; Rust, John; Wong, Kin-Ping
    Published: [2023]
    Publisher:  SSRN, [S.l.] ; Georgetown University, Department of Economics, Washington, DC

    Are the serves of the world’s best tennis pros consistent with the theoretical predictions of Nash equilibrium in mixed strategies? We analyze their serve direction choices (to the receiver’s left, right or body) with data from an online database... more

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    Are the serves of the world’s best tennis pros consistent with the theoretical predictions of Nash equilibrium in mixed strategies? We analyze their serve direction choices (to the receiver’s left, right or body) with data from an online database called the Match Charting Project. Using a new methodology, we test and decisively reject a key implication of a mixed strategy Nash equilibrium, namely, that the probability of winning a service game is the same for all serve directions. We also use dynamic programming (DP) to numerically solve for the best-response serve strategies in models of the service game of tennis estimated for individual server-receiver pairs, such as Novak Djokovic serving to Rafael Nadal. We show that for most elite professional servers, the DP serve strategy significantly increases their service game win probability compared to the mixed strategies they actually use, which we estimate using flexible reduced-form logit models. Stochastic simulations verify that our results are robust to estimation error

     
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    Series: Working papers / Georgetown University, Department of Economics ; 23-23-03
    Subjects: tennis; games; Nash equilibrium; Minimax theorem; constant sum games; mixed strategies; dynamic directional games; binary Markov games; dynamic programming; structural estimation; muscle memory; magnification effect
    Scope: 1 Online-Ressource (circa 84 Seiten)
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    Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments March 9, 2023 erstellt
  6. A dedicated pricing algorithm to solve a large family of nurse scheduling problems with branch-and-price
    Author: Legrain, Antoine; Omer, Jérémy
    Published: [2023]
    Publisher:  GERAD, HÉC Montréal, Montréal (Québec), Canada

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    Series: Les cahiers du GERAD ; G-2023, 02 (January 2023)
    Subjects: Nurse scheduling; column-generation; decomposition; branch-and-price; dynamic programming; soft constraints
    Scope: 1 Online-Ressource (circa 33 Seiten), Illustrationen
  7. Optimal additional voluntary contribution in DC pension schemes to manage inadequacy risk
    Author: Ferreira Morici, Henrique; Vigna, Elena
    Published: [2023]
    Publisher:  CCA, Fondazione Collegio Carlo Alberto, Torino

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    Series: Carlo Alberto notebooks ; no. 699 (September 2023)
    Subjects: Stochastic optimal control; dynamic programming; defined contribution pension scheme; additional voluntary contributions; target-based approach; net replacement ratio
    Scope: 1 Online-Ressource (circa 41 Seiten), Illustrationen
  8. Dynamic programming for valuing options embedded in corporate bonds
    Author: Ben-Abdellatif, Malek; Ben-Ameur, Hatem; Chérif, Rim; Fakhfakh, Tarek
    Published: [2023]
    Publisher:  GERAD, HÉC Montréal, Montréal (Québec), Canada

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    Series: Les cahiers du GERAD ; G-2023, 58 (November 2023)
    Subjects: Structural models; corporate securities; options embedded in corporate bonds; dynamic programming; finite elements
    Scope: 1 Online-Ressource (circa 17 Seiten), Illustrationen
  9. Resource loading with time windows
    Published: 2014
    Publisher:  KU Leuven, Fac. of Business and Economics, Leuven

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    Series: KBI ; 1402
    Subjects: Dynamische Optimierung; Resource loading; dynamic programming; np-complete; preemption; approximation algorithms
    Scope: Online-Ressource (26 S.)
  10. Exact and inexact scheduling algorithms for multiple earth observation satellites under uncertainties of clouds
    Published: 2015
    Publisher:  KU Leuven, Fac. of Economics and Business, Leuven

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    Series: KBI ; 1514
    Subjects: earth observation satellites; uncertainties of clouds; model decomposition,enumeration; dynamic programming; heuristic
    Scope: Online-Ressource (28 S.), graph. Darst.
  11. Sustainability of pension schemes
    building a smooth automatic balance mechanism with an application to the US social security
    Author: Gannon, Frédéric; Legros, Florence; Touze, Vincent
    Published: May 2016
    Publisher:  OFCE, [Paris]

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    Series: Working paper / OFCE ; 2016, 16
    Subjects: Pensions scheme sustainability; automatic balance mechanisms; dynamic programming
    Scope: 1 Online-Ressource (circa 29 Seiten), Illustrationen
  12. Modeling poset convex subsets
    Author: Queyranne, Maurice; Wolsey, Laurence A.
    Published: November 26, 2015
    Publisher:  Centre for Operations Research and Econometrics, Louvain-la-Neuve

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    Other identifier:
    hdl: 2078.1/167579
    Series: CORE discussion paper ; 2015, 49
    Subjects: partial order; convex subsets; extended formulation; convex hull; separation algorithms; dynamic programming
    Scope: 1 Online-Ressource (circa 20 Seiten)
  13. A fast upper envelope scan method for discrete-continuous dynamic programming
    Author: Dobrescu, Loretti Isabella; Shanker, Akshay
    Published: [2023]
    Publisher:  CEPAR, ARC Centre of Excellence in Population Ageing Research, [Kensington, NSW]

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    Series: Working paper / CEPAR, ARC Centre of Excellence in Population Ageing Research ; 2023, 04
    Subjects: discrete and continuous choices; non-convex optimization; Euler equation; computational methods; dynamic programming
    Scope: 1 Online-Ressource (circa 49 Seiten), Illustrationen
  14. Crowdshipping: an open VRP variant with stochastic destinations
    Author: Torres, Fabian; Genreau, Michel; Rei, Walter
    Published: November 2021
    Publisher:  Bureau de Montreal, Université de Montreal, Montréal (Québec)

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    Series: CIRRELT ; CIRRELT-2021, 46
    Subjects: Crowd-shipping; crowd-logistics; crowd drivers; occasional drivers; city logistics; stochastic programming; dynamic programming; column generation
    Scope: 1 Online-Ressource (circa 34 Seiten), Illustrationen
  15. Bellman filtering for state-space models
    Author: Lange, Rutger-Jan
    Published: [2021]
    Publisher:  Tinbergen Institute, Amsterdam, The Netherlands

    This article presents a new filter for state-space models based on Bellman's dynamic programming principle applied to the posterior mode. The proposed Bellman filter generalises the Kalman filter including its extended and iterated versions, while... more

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    This article presents a new filter for state-space models based on Bellman's dynamic programming principle applied to the posterior mode. The proposed Bellman filter generalises the Kalman filter including its extended and iterated versions, while remaining equally inexpensive computationally. The Bellman filter is also (unlike the Kalman filter) robust under heavy-tailed observation noise and applicable to a wider range of models. Simulation studies reveal that the mean absolute error of the Bellman-filtered states using estimated parameters typically falls within a few percent of that produced by the mode estimator evaluated at the true parameters, which is optimal but generally infeasible.

     
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    Other identifier:
    hdl: 10419/229672
    Edition: Revision: 8 January 2021
    Series: Array ; TI 2020, 052
    Subjects: Bellman filter; dynamic programming; Kalman filter; maximum a posteriori (MAP)estimate; posterior mode; state-space model
    Scope: 1 Online-Ressource (circa 26 Seiten)
  16. Precedence theorems and dynamic programming for the single-machine weighted tardiness problem
    Author: Rostami, Salim; Creemers, Stefan; Leus, Roel
    Published: [2017]
    Publisher:  KU Leuven, Faculty of Economics and Business, Leuven, België

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    Format: Online
    Series: KBI ; KBI_17, 15
    Subjects: single-machine scheduling; precedence constraints; weighted tardiness; precedence theorems; dynamic programming
    Scope: 1 Online-Ressource (circa 21 Seiten)
  17. Exploiting symmetry in high-dimensional dynamic programming
    Author: Kahou, Mahdi Ebrahimi; Fernández-Villaverde, Jesús; Perla, Jesse; Sood, Arnav
    Published: June 2021
    Publisher:  CESifo, Center for Economic Studies & Ifo Institute, Munich, Germany

    We propose a new method for solving high-dimensional dynamic programming problems and recursive competitive equilibria with a large (but finite) number of heterogeneous agents using deep learning. The "curse of dimensionality" is avoided due to four... more

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    We propose a new method for solving high-dimensional dynamic programming problems and recursive competitive equilibria with a large (but finite) number of heterogeneous agents using deep learning. The "curse of dimensionality" is avoided due to four complementary techniques: (1) exploiting symmetry in the approximate law of motion and the value function; (2) constructing a concentration of measure to calculate high-dimensional expectations using a single Monte Carlo draw from the distribution of idiosyncratic shocks; (3) sampling methods to ensure the model fits along manifolds of interest; and (4) selecting the most generalizable over-parameterized deep learning approximation without calculating the stationary distribution or applying a transversality condition. As an application, we solve a global solution of a multi-firm version of the classic Lucas and Prescott (1971) model of "investment under uncertainty." First, we compare the solution against a linear-quadratic Gaussian version for validation and benchmarking. Next, we solve nonlinear versions with aggregate shocks. Finally, we describe how our approach applies to a large class of models in economics.

     
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    hdl: 10419/236703
    Series: CESifo working paper ; no. 9161 (2021)
    Subjects: dynamic programming; deep learning; breaking the curse of dimensionality
    Scope: 1 Online-Ressource (circa 50 Seiten), Illustrationen
  18. Disequilibrium play in tennis
    Author: Anderson, Axel; Rosen, Jeremy; Rust, John; Wong, Kin-Ping
    Published: 2021
    Publisher:  Georgetown University, Department of Economics, Washington, DC

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    Series: Working papers / Georgetown University, Department of Economics ; 21, 07
    Subjects: tennis; games; Nash equilibrium; Minimax theorem; constant sum games; mixed strategies; dynamic directional games; binary Markov games; dynamic programming; structural estimation; muscle memory
    Scope: 1 Online-Ressource (circa 63 Seiten), Illustrationen
  19. A lifted-space dynamic programming algorithm for the Quadratic Knapsack Problem
    Author: Fomeni, Franklin Djeumou
    Published: [2021]
    Publisher:  GERAD, HÉC Montréal, Montréal (Québec), Canada

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    Series: Les cahiers du GERAD ; G-2021, 27 (May 2021)
    Subjects: Knapsack problems; integer programming; dynamic programming; local search; binary quadratic optimization
    Scope: 1 Online-Ressource (circa 19 Seiten), Illustrationen
  20. Pricing climate risk
    Author: Jensen, Svenn; Traeger, Christian
    Published: July 2021
    Publisher:  CESifo, Center for Economic Studies & Ifo Institute, Munich, Germany

    Anthropogenic greenhouse gas emissions are changing the energy balance of our planet. Various climatic feedbacks make the resulting warming over the next decades and centuries highly uncertain. We quantify how this uncertainty changes the optimal... more

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    Anthropogenic greenhouse gas emissions are changing the energy balance of our planet. Various climatic feedbacks make the resulting warming over the next decades and centuries highly uncertain. We quantify how this uncertainty changes the optimal carbon tax in a stochastic dynamic programming implementation of an integrated assessment model of climate change. We derive a general analytic formula for the "risk premium" governing the resulting climate policy. The formula generalizes simple precautionary savings analysis to more complex economic interactions and it builds the economic intuition for policy making under uncertainty. It clarifies the distinct roles of risk aversion, prudence, characteristics of the damage formulation, and future policy response. We show that an optimal response to uncertainty substantially reduces the risk premium.

     
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    hdl: 10419/245377
    Series: CESifo working paper ; no. 9196 (2021)
    Subjects: climate change; uncertainty; risk premium; precautionary savings; prudence; climate policy; dynamic programming; integrated assessment; DICE; recursive utility
    Scope: 1 Online-Ressource (circa 66 Seiten), Illustrationen
  21. Smart cap
    Author: Karp, Larry S.; Traeger, Christian
    Published: February 2021
    Publisher:  CESifo, Center for Economic Studies & Ifo Institute, Munich, Germany

    We introduce a "smart" cap and trade system that eliminates the welfare costs of asymmetric information (“uncertainty”). This cap responds endogenously to technology or macroeconomic shocks, relying on the market price of certificates to aggregate... more

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    We introduce a "smart" cap and trade system that eliminates the welfare costs of asymmetric information (“uncertainty”). This cap responds endogenously to technology or macroeconomic shocks, relying on the market price of certificates to aggregate information. It allows policy makers to modify existing institutions to achieve more efficient emission reductions. The paper also shows that the efficient carbon price is more sensitive to technological innovations than usually assumed. The lasting impact and slow diffusion of these innovations typically make the optimal carbon price a much steeper function of emissions than suggested by the social cost of carbon.

     
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    hdl: 10419/235287
    Series: CESifo working paper ; no. 8917 (2021)
    Subjects: pollution; climate change; taxes; quantities; regulation; smart cap; uncertainty; technology diffusion; dynamic programming; integrated assessment; DICE
    Scope: 1 Online-Ressource (circa 63 Seiten), Illustrationen