Simulation optimization (SO) refers to the optimization of an objective function subject to
constraints, both of which can be evaluated through a stochastic simulation. To address …

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 …

Metaheuristics are widely recognized as efficient approaches for many hard optimization
problems. This paper provides a survey of some of the main metaheuristics. It outlines the …

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

Simulated annealing (SA) presents an optimization technique with several striking positive
and negative features. Perhaps its most salient feature, statistically promising to deliver an …

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 …

Now in Its Fourth Edition: Your Guide to Successful Facility Design Overcome design and
planning problems using the fourth edition of Facilities Design. Dedicated to the proper …

Still today I am receiving requests for reprints of the book, but unfortunately it is out of print.
Therefore, since the book still seems to receive some attention, I p-posed to Springer Verlag …

We present a new LP formulation for the single allocation p-hub median problem, which
requires fewer variables and constraints than those traditionally used in the literature. We …