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MAX-MIN Ant System
TLDR
In this paper, we present MAX – MIN Ant System, an Ant Colony Optimization algorithm derived from Ant System. Expand
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Ant Colony Optimization Theory
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Ant colony optimization: artificial ants as a computational intelligence technique
TLDR
The introduction of ant colony optimization (ACO) and to survey its most notable applications are discussed. Expand
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ParamILS: An Automatic Algorithm Configuration Framework
TLDR
We describe an automatic framework for this algorithm configuration problem and present novel techniques for accelerating them by adaptively limiting the time spent for evaluating individual configurations. Expand
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A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem
TLDR
In this work we present a new iterated greedy algorithm that applies two phases iteratively, named destruction, were some jobs are eliminated from the incumbent solution. Expand
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Stochastic Local Search: Foundations & Applications
TLDR
Prologue Part I. Foundations 1. Introduction 2. SLS Methods 3. Generalised Local Search Machines 4. Empirical Analysis of SLS Algorithms 5. Applications 6. SAT and Constraint Satisfaction 7. MAX-SAT and MAX-CSP. Expand
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Empirical Scoring Functions for Advanced Protein-Ligand Docking with PLANTS
TLDR
We present two empirical scoring functions, PLANTS(CHEMPLP) and PLANETS(PLP), designed for our docking algorithm PLANTS (Protein-Ligand ANT System), which is based on ant colony optimization (ACO). Expand
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The irace package: Iterated racing for automatic algorithm configuration
TLDR
In this paper, we describe the rationale underlying the iterated racing procedures of the irace package and introduce a number of recent extensions. Expand
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The Ant Colony Optimization Metaheuristic: Algorithms, Applications, and Advances
TLDR
The field of ACO algorithms is very lively, as testified, for example, by the successful biannual workshop (ANTS—From Ant Colonies to Artificial Ants: A Series of International Workshops on Ant Algorithms; http://iridia.ulb.ac.be/~ants/) where researchers meet to discuss the properties of ACo and other ant algorithms. Expand
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A Racing Algorithm for Configuring Metaheuristics
TLDR
This paper describes a racing procedure for finding, in a limited amount of time, a configuration of a metaheuristic that performs as good as possible on a combinatorial optimization problem. Expand
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