An efficient implementation of the simulated annealing heuristic for the quadratic assignment problem

TL;DR

This paper introduces a highly efficient implementation of the simulated annealing heuristic for the quadratic assignment problem, significantly reducing computation time for large instances.

Contribution

The authors develop an implementation of simulated annealing that is over 100 times faster than previous methods for large QAP instances.

Findings

Over 100x speedup for large problem sizes

Maintains solution quality with increased efficiency

Applicable to large-scale quadratic assignment problems

Abstract

The quadratic assignment problem (QAP) is one of the most difficult combinatorial optimization problems. One of the most powerful and commonly used heuristics to obtain approximations to the optimal solution of the QAP is simulated annealing (SA). We present an efficient implementation of the SA heuristic which performs more than 100 times faster then existing implementations for large problem sizes and a large number of SA iterations.