Simulated annealing is a probabilistic method proposed in Kirkpatrick, Gelett and Vecchi
(1983) and Cerny (1985) for finding the global minimum of a cost function that may possess …

This paper describes the Simulated Annealing algorithm and the physical analogy on which
it is based. Some significant theoretical results are presented before describing how the …

The growth of artificial intelligence leads to a computational burden in solving non-
deterministic polynomial-time (NP)-hard problems. The Ising computer, which aims to solve …

This paper proposes a crowdsource-enabled system for urban parcel relay and delivery. We
consider cyclists and pedestrians as crowdsources who are close to customers and …

Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial
optimization and neural computing | Guide books skip to main content ACM Digital Library home …

Human intelligence is the intellectual prowess of humans, which is marked by four basic and
important abilities: learning ability, cognition (acquiring and storing knowledge) ability …

Despite increasing interest in Bayesian approaches, especially across the social sciences, it
has been virtually impossible to find a text that introduces Bayesian data analysis in a …

In this and two companion papers, we report on an extended empirical study of the
simulated annealing approach to combinatorial optimization proposed by S. Kirkpatrick et al …

Metaheuristics are the most exciting development in approximate optimization techniques of
the last two decades. They have had widespread successes in attacking a variety of difficult …

Algorithms for VLSI Physical Design Automation, Second Edition is a core reference text for
graduate students and CAD professionals. Based on the very successful First Edition, it …