915 research outputs found
Endowments, patience types, and uniqueness in two-good HARA utility economies
No full textThis paper establishes a link between endowments, patience types, and the parameters of the HARA Bernoulli utility function that ensure equilibrium uniqueness in an economy with two goods and two impatience types with additive separable preferences. We provide sufficient conditions that guarantee uniqueness of equilibrium for any possible value of γ in the HARA utility function γ 1−γ b+ a
γx 1−γ. The analysis contributes to the literature on uniqueness in pure exchange economies with two-goods and two agent types and extends the result in Loi and Matta (2022)
Increasing complexity in structurally stable models: an application to a pure exchange economy
No full textA model M is defined (see Anderlini and Canning (2001) and Yu et al. (2009)) as a quadruple M = {Lambda, X, F, R}, where Lambda and X represent the parameter and actions spaces, respectively, F is a correspondence defining the feasible actions and R is a real-valued function which measures the degree of rationality of the feasible actions. We recall that structural stability means the continuity of the equilibrium set with respect to small perturbations of the parameters and that robustness to bounded rationality holds if small deviations from rationality imply small changes in the equilibrium set. In this paper we extend to a model (M) over bar = {(Lambda) over bar, (X) over bar, (F) over bar, (R) over bar}, where (Lambda) over bar is defined as the set of all compact subsets of A, (X) over bar = X, (F) over bar and (R) over bar are the feasibility and rationality correspondences which extend F and R, respectively. (M) over bar is more complex than M, since M is embedded into (M) over bar in a natural way. We show that the structural stability of A implies the structural stability of (M) over bar and that (M) over bar is robust to bounded rationality if (R) over bar is lower semi-continuous. This abstract characterization of complexity is important because it can be used to appraise the nontrivial issue of whether structural stability and robustness to bounded rationality are preserved when a structurally stable model M is extended to (M) over bar. By applying this abstract construction to a pure exchange economy, the result by Loi and Matta (2010), concerning the stability of the equilibrium set with respect to perturbations of endowments along a given path, is extended to perturbations of paths under bounded rationality. (C) 2015 Elsevier B.V. All rights reserved
Simulation optimization with mathematical programming representation of discrete event systems
No full textMathematical programming time-based decomposition algorithm for discrete event simulation
No full textMathematical programming has been proposed in the literature as an alternative technique to simulating a special class of Discrete Event Systems. There are several benefits to using mathematical programs for simulation, such as the possibility of performing sensitivity analysis and the ease of better integrating the simulation and optimisation. However, applications are limited by the usually long computational times. This paper proposes a time-based decomposition algorithm that splits the mathematical programming model into a number of submodels that can be solved sequentially to make the mathematical programming approach viable for long running simulations. The number of required submodels is the solution of an optimisation problem that minimises the expected time for solving all of the submodels. In this way, the solution time becomes a linear function of the number of simulated entities. © 2013 Elsevier B.V. All rights reserved
A decomposition approach for the home health care problem with time windows
No full textOptimization tools are necessary to efficiently plan service delivery for patients at home in the context of Home Health Care services. In the scientific literature, Periodic Vehicle Routing Problem with Time Windows (PVRPTW) is proposed to address the assignment, scheduling and routing processes with time windows. However, PVRPTW is computationally difficult and not viable for large-size problems. Thus, a practical approach is proposed to decompose the problem. Time windows are considered at the assignment level using a probabilistic model without the need of solving the routing problem. Mixed integer mathematical programming models are proposed and solved by CPLEX solver. Numerical experiments are executed to validate the performance of the proposed models with respect to the PVRPTW
An Analytical Method for the Performance Evaluation of Flexible Manufacturing Systems with Deterministic Processing Times
No full textIntegrated simulation-optimisation of pull control systems
No full textPull policies are considered to be among the most efficient control strategy. Setting the correct parameters to maximise their efficiency is, however, not a trivial task. Simulation–optimisation techniques have received particular attention as a means to solve this problem. Nevertheless, they require the iterative solution of an optimisation model to generate the parameter values and a discrete event simulator to evaluate the resulting system performance. In the framework of simulation-optimisation, this paper proposes a combined solution of the optimisation and simulation problems for the optimal operation of pull control systems under several control strategies. Numerical experiments were performed to evaluate the performance of the proposed technique
Integrating Simulation Modeling and Optimization: an Event Based Approach
No full textThe optimization of stochastic Discrete Event Systems (DESs) is a critical and diffcult task. Besides the search for the optimal system configuration, it requires the assessment of the system performance. In fact, both simulation and optimization need to be performed, resulting in a simulation-optimization problem. In the past ten years, a noticeable research effort has been devoted to this problem. Recently, mathemathical programming has been proposed to integrate simulation and optimization by means of event-based mathematical models. This paper proposes a general approach that adopts event-based mathematical programming models to simultaneously simulate and optimize the system leading to what we define Discrete Event Optimization. Formal results are given to derive the integrated simulation-optimization models and the related properties are illustrated
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