simulated annealing
PulseAugur coverage of simulated annealing — every cluster mentioning simulated annealing across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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New Langevin-gradient method accelerates global optimization for non-convex functions
Researchers have developed a new approach to global optimization for smooth, non-convex functions, aiming to find the absolute minimum value with a specified probability. The proposed Langevin--gradient method separates…
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New research explores hybrid neural solvers for combinatorial optimization
Two new research papers explore advanced neural network approaches for combinatorial optimization problems. The first paper introduces HyCO, a hybrid solver that combines reinforcement learning with diffusion models to …
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GNNs and adaptive penalties boost quantum annealing for routing problems
Researchers have developed a novel approach to improve the efficiency of solving the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) on quantum annealers. Their method utilizes graph neural networks (GNNs…
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New T3L-DS method optimizes emergency scheduling for LEO Earth observation constellations
Researchers have developed a new method called Task-Driven Three-Layer Distributed Scheduling (T3L-DS) to address the dynamic emergency observation scheduling problem (DEOSP) in large low-Earth-orbit (LEO) Earth-observa…
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Leaders urged to adopt strategic, quantum-inspired computing path
Business leaders are advised to adopt a strategic and measured approach to quantum computing, focusing on quantum-inspired techniques that can be implemented on current classical hardware. These techniques, such as quan…
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AI framework tackles airport traffic congestion, cutting queues by up to 30%
Researchers have developed a computational framework inspired by QUBO to diagnose and optimize traffic flow in airport landside areas. This model, tested using data from Shanghai Pudong and Hangzhou Xiaoshan Internation…
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New GNN-GA algorithm optimizes Physical Internet supply chains
Researchers have developed a novel Graph Neural Network--Guided Genetic Algorithm (GNN-GA) to optimize complex supply chain networks within the Physical Internet framework. This approach combines discrete assignment dec…
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New Bayesian Optimization Method Enhances Spectroscopic Data Analysis
Researchers have developed a new method for selecting optimal wavelengths in near-infrared spectroscopy, crucial for improving the accuracy and interpretability of spectral data in tasks like sugar content estimation. T…
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New heuristics improve radiotherapy scheduling efficiency
Researchers have developed new heuristic methods, RTSP First Fit and RTSP Best Fit, to optimize radiotherapy scheduling, addressing limitations of existing integer linear programming models. These heuristics, when combi…
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New benchmark BBOPlace-Bench advances AI for chip placement
Researchers have introduced BBOPlace-Bench, a novel benchmark designed to evaluate and advance black-box optimization (BBO) algorithms specifically for chip placement tasks. This benchmark addresses a gap in existing to…
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New ARDL model embeds fairness in retail pricing strategies
Researchers have developed a new methodology for dynamic pricing in retail that incorporates fairness constraints to balance profitability with consumer welfare. The approach uses a log-log Autoregressive Distributed La…
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New heuristic matches advanced routing algorithms with vastly reduced computation
Researchers have developed a new reward-density heuristic, termed the Efficiency heuristic, for dynamic multi-vehicle routing problems. This heuristic aims to maximize cumulative reward collected by a fleet of vehicles …
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New tool synthesizes probabilistic processors using Ising model for optimization
Researchers have developed a new tool designed to synthesize and simulate probabilistic processors that leverage the Ising model for solving complex combinatorial optimization problems. This tool automatically generates…
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New conservation law quantifies program discovery costs
A new paper introduces a conservation law for program discovery, suggesting that injecting structural knowledge into a search algorithm trades off directly against the search effort. This law quantifies the cost of find…
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Metaheuristic Algorithms Optimize Appliance Scheduling for Solar Energy
This paper introduces a metaheuristic approach using Iterated Local Search (ILS) and Simulated Annealing (SA) to optimize appliance scheduling for solar energy management. The goal is to maximize the utilization of sola…
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New Caching Techniques Boost LLM and Diffusion Model Efficiency
Researchers have developed MiniPIC, a new method for efficient caching in large language model inference that requires fewer than 100 lines of code changes to existing systems like vLLM. This approach improves prefill t…