Open AccessPosted Content
Criticality and Parallelism in Combinatorial Optimization
TLDR
The existence of a phase transition in combinatorial optimization problems was shown in this paper, where the quality of local search algorithms degrades to no better than random search for a family of generalized spin-glass models and the traveling salesman problem.Abstract:
We demonstrate the existence of a phase transition in combinatorial optimization problems. For many of these problems, as local search algorithms are parallelized, the quality of solutions first improves and then sharply degrades to no better than random search. This transition can be successfully characterized using finite-size scaling, a technique borrowed from statistical physics. We demonstrate our results for a family of generalized spin-glass models and the Traveling Salesman Problem. We determine critical exponents, investigate the effects of noise, and discuss conditions for the existence of the phase transition.read more
Citations
More filters
Journal ArticleDOI
Heuristic recurrent algorithms for photonic Ising machines
Charles Roques-Carmes,Yichen Shen,Cristian Zanoci,Mihika Prabhu,Fadi Atieh,Li Jing,Tena Dubček,Chenkai Mao,Miles R. Johnson,Vladimir Ceperic,John D. Joannopoulos,Dirk Englund,Marin Soljacic +12 more
TL;DR: This work presents the Photonic Recurrent Ising Sampler (PRIS), a heuristic method tailored for parallel architectures allowing fast and efficient sampling from distributions of arbitrary Ising problems, and suggests speedups in heuristic methods via photonic implementations of the PRIS.
Proceedings Article
Emergence of profitable search strategies based on a simple inheritance mechanism
Natalio Krasnogor,James C. Smith +1 more
TL;DR: A simple vertical inheritance mechanism is enough to provide a robust adaptation of behavior and this result s-pans from a simple OneMax problem, to NK-landscapes and the TSP.
Distributed Stochastic Search for Constraint Satisfaction and Optimization: Parallelism, Phase Transitions and Performance
TL;DR: This research studies an existing distributed search method, called distributed stochastic algorithm (DSA), and its variations for solving distributed CSPs and COPs, and shows that DSAs are generally more effective and efficient than distributed breakout algorithm on many network structures, particularly on over-constrained structures, finding better solutions and having lower communication cost.
Proceedings ArticleDOI
Distributed algorithms for sleep scheduling in wireless sensor networks
S. Chachra,Michael M. Marefat +1 more
TL;DR: Several distributed algorithms are proposed to perform sensor and radio sleep scheduling in wireless sensor networks while trying to minimize its negative impact.
Proceedings ArticleDOI
Survey on computational complexity with phase transitions and extremal optimization
Guo-Qiang Zeng,Yong-Zai Lu +1 more
TL;DR: This survey reviews the latest research results from fundamental to practice about the connection between computational complexity and phase transitions, and introduces the concepts, fundamentals, algorithms and applications of extremal optimization from its capability of self-organized criticality, backbone analysis and co-evolution moving to a far-from-equilibrium state.