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Discrete optimization

About: Discrete optimization is a research topic. Over the lifetime, 4598 publications have been published within this topic receiving 158297 citations. The topic is also known as: discrete optimisation.


Papers
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Proceedings ArticleDOI
10 May 1992
TL;DR: A heuristic algorithm based on Lagrangian optimization and using an operational rate-distortion framework that, with much-reduced computing complexity, approaches the optimally achievable SNR is provided.
Abstract: The description of the buffer-constrained quantization problem is formalized. For a given set of admissible quantizers for coding a discrete nonstationary signal sequence in a buffer-constrained environment, and for any global distortion minimization criterion that is additive over the individual elements of the sequence, the optimal solution and slightly suboptimal but much faster approximations are formulated. The problem is first defined as one of constrained, discrete optimization, and its equivalence to some problems in integer programming is established. Dynamic programming using the Viterbi algorithm is shown to provide a way of computing the optimal solution. A heuristic algorithm based on Lagrangian optimization and using an operational rate-distortion framework that, with much-reduced computing complexity, approaches the optimally achievable SNR is provided. >

45 citations

Journal ArticleDOI
TL;DR: Simulation results demonstrate that the proposed swarm reinforcement learning (SRL) can obtain a larger total benefit than genetic algorithm (GA), particle swarm optimization (PSO), grasshopper optimization algorithm (GOA), harris hawks optimizer (HHO), butterfly optimization algorithms (BOA), and Q-learning, in which the benefit increment can reach from 2.12% ( against PSO) to 10.62% (against Q- learning).

45 citations

Journal ArticleDOI
TL;DR: In this article, the development of a production control strategy for a custom door manufacturer is investigated, and a Kanban system is developed for the production environment, which is applied to a production environment which neither represents a pure flow shop nor contains balanced production processes.
Abstract: This paper investigates the development of a production control strategy for a custom door manufacturer. A Kanban system is developed for the production environment. Simulation and discrete optimization techniques are applied to configure the system. The paper demonstrates that a Kanban approach can be applied to a production environment which neither represents a pure flow shop nor contains balanced production processes. It also highlights the difficulties that can arise in performing a discrete optimization upon conflicting multiple stochastic responses.

45 citations

Journal ArticleDOI
TL;DR: In this paper, an approach for dynamic optimization considering uncertainties is developed and applied to robust aircraft trajectory optimization, and the nonintrusive polynomial chaos expansion scheme is employed to convert a robust trajectory optimization problem with stochastic ordinary differential equations into an equivalent deterministic trajectory optimized problem with deterministic ordinary differential equation.
Abstract: The development of algorithms for aircraft robust dynamic optimization considering uncertainties (for example, trajectory optimization) is relatively limited compared to aircraft robust static optimization (for example, configuration shape optimization). In this paper, an approach for dynamic optimization considering uncertainties is developed and applied to robust aircraft trajectory optimization. In the present approach, the nonintrusive polynomial chaos expansion scheme is employed to convert a robust trajectory optimization problem with stochastic ordinary differential equations into an equivalent deterministic trajectory optimization problem with deterministic ordinary differential equations. Two computational strategies for trajectory optimization considering uncertainties are compared. The performance of the developed method is studied by considering a classical deterministic trajectory optimization problem of supersonic aircraft short-time climb with uncertainties in the aerodynamic data. Detailed...

45 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202313
202236
2021104
2020128
2019113
2018140