Revisiting Simulated Annealing: a Component-Based Analysis

by Alberto Franzin and Thomas Stützle

Table of Contents
  1. Abstract
  2. Supplementary Material (PDF)
  3. Instance Files
  4. Parameter File

1. Abstract:

Simulated Annealing (SA) is one of the oldest metaheuristics and has been adapted to solve many combinatorial optimization problems. Over the years, many authors have proposed both general and problem-specific improvements and variants of SA. We propose to accumulate this knowledge into automatically configurable, algorithmic frameworks so that for new applications that wealth of alternative algorithmic components is directly available for the algorithm designer without further manual intervention. To do so, we describe SA as an ensemble of algorithmic components, and describe SA variants from the literature within these components. We show the advantages of our proposal by (i) implementing existing algorithmic components of variants of SA, (ii) studying SA algorithms proposed in the literature, (iii) improving SA performance by automatically designing new state-of-the-art SA implementations and (iv) studying the role and impact of the algorithmic components based on experimental data. We experimentally demonstrate the potential of this approach on three common combinatorial optimization problems, the quadratic assignment problem and two variants of the permutation flow shop problem.

Keywords: Simulated Annealing; Metaheuristics; Automatic Algorithm Design; Automatic Algorithm Configuration; Empirical Analysis.

2. Supplementary Material:


3. Instance Files:

QAP training set (4.4 MB) and testing set (4.4 MB). In each archive there are 150 random instances and 150 structured instances, equally divided in instances of size 60, 80, 100 taken from IridiaSupp2010-009.

PFSP training set (260 KB) and testing set (404 KB). The test set is the common Taillard benchmark.

4. Parameter File:

The list of parameter definitions, formatted as irace parameter file and including names, type and range for all the components and numerical parameters of this work, is available here.