Ant System, the first Ant Colony Optimization algorithm, showed to be a viable method for attacking hard combinatorial optimization problems. Yet, its performance, when compared to more fine-tuned algorithms, was rather poor for large instances of traditional benchmark problems like the Traveling Salesman Problem. To show that Ant Colony Optimization algorithms could be good alternatives to existing algorithms for hard combinatorial optimization problems, recent research in this ares has mainly focused on the development of algorithmic variants which achieve better performance than AS. In this article, we present MAX--MIN Ant System, an Ant Colony Optimization algorithm derived from Ant System. MAX--MIN Ant System differs from Ant System in several important aspects, whose usefulness we demonstrate by means of an experimental study. Additionally, we relate one of the characteristics specific to MMAS--- that of using a greedier search than Ant System--- to results from the search space analysis of the combinatorial optimization problems attacked in this paper. Our computational results on the Traveling Salesman Problem and the Quadratic Assignment Problem show that MAX--MIN Ant System is currently among the best performing algorithms for these problems. 1
|
7711
|
Computers and Intractability: A Guide to the Theory of NP-Completeness
– Garey, Johnson
- 1979
|
|
479
|
Ant system: optimization by a colony of cooperating agents
– Dorigo, Maniezzo, et al.
- 1996
|
|
342
|
Ant colony system: A cooperative learning approach to the traveling salesman problem
– Dorigo, Gambardella
- 1997
|
|
273
|
The Traveling Salesman problem
– Lawler, Lenstra
- 1984
|
|
248
|
An Effective Heuristic Algorithm for the Traveling Salesman Problem
– Lin, Kernighan
- 1973
|
|
215
|
G.: The Ant Colony Optimization Meta-heuristic
– Dorigo, Caro
- 1999
|
|
215
|
The Traveling Salesman Problem: A Case Study in Local Optimization
– Johnson, McGeoch
- 1997
|
|
197
|
Computer Solutions on the Travelling Salesman Problem
– Lin
- 1965
|
|
187
|
P-Complete Approximation problems
– Sahni, Gonzalez
- 1976
|
|
138
|
AntNet: Distributed stigmergetic control for communications networks
– Caro, Dorigo
- 1998
|
|
135
|
The Traveling Salesman: Computational Solutions for TSP Applications
– Reinelt
- 1994
|
|
128
|
Fitness Distance Correlation as a Measure of Problem Difficulty for Genetic Algorithms
– Jones, Forrest
- 1995
|
|
122
|
Fast algorithms for geometric traveling salesman problems
– Bentley
- 1992
|
|
105
|
Correlated and uncorrelated fitness landscapes and how to tell the difference
– Weinberger
- 1990
|
|
100
|
The ant system applied to the quadratic assignment problem
– Maniezzo, Colorni
- 1999
|
|
99
|
Evolution in Time and Space – The Parallel Genetic Algorithm
– Mühlenbein
- 1991
|
|
95
|
A new adaptive multi-start technique for combinatorial global optimization
– Boese, Kahng, et al.
|
|
85
|
Robust taboo search for the quadratic assignment problem
– Taillard
- 1991
|
|
84
|
Large-step Markov chains for the traveling salesman problem
– Martin, Otto, et al.
- 1991
|
|
77
|
Maniezzo V, Colorni A: Positive feedback as a search strategy
– Dorigo
|
|
77
|
Combining simulated annealing with local search heuristics
– Martin, Otto
- 1996
|
|
74
|
MACS-VRPTW: A multiple ant colony system for vehicle routing problems with time windows
– Gambardella, Taillard, et al.
- 1999
|
|
73
|
Dorigo M, Ant-Q: a reinforcement learning approach to the traveling salesman problem
– Gambardella
- 1995
|
|
72
|
Genetic hybrids for the quadratic assignment problem
– Ferland
- 1994
|
|
65
|
Comparison of iterative searches for the quadratic assignment problem
– Taillard
- 1995
|
|
63
|
The MAX-MIN Ant System and Local Search for the Traveling Salesman Problem
– Stützle, Hoos
- 1997
|
|
62
|
An improved ant system algorithm for the vehicle routing problem
– Bullnheimer, Hartl, et al.
- 1999
|
|
61
|
Genetic Local Search for the TSP: New Results
– Merz, Freisleben
- 1997
|
|
55
|
Genetic Local Search Algorithms for the Traveling Salesman Problem
– Ulder, Aarts, et al.
- 1990
|
|
52
|
Towards a theory of landscapes
– Stadler
- 1995
|
|
48
|
Solving Symmetric and Asymmetric TSPs by Ant Colonies
– Gambardella, Dorigo
- 1996
|
|
48
|
Local Search Algorithms for Combinatorial Problems — Analysis, Improvements, and New Applications
– Stützle
- 1998
|
|
45
|
A Genetic Local Search Algorithm for Solving Symmetric and Asymmetric Traveling Salesman Problems
– Freisleben, Merz
- 1996
|
|
44
|
Ant colonies for the qap
– Gambardella, Taillard, et al.
- 1997
|
|
44
|
Fitness landscape and memetic algorithm design
– Merz, Freisleben
- 1999
|
|
42
|
Exact and Approximate Nondeterministic Tree-search Procedures for the Quadratic Assignment Problem
– Maniezzo
- 1998
|
|
42
|
Edge assembly crossover: A high-power genetic algorithm for the traveling salesman problem
– Nagata, Kobayashi
- 1997
|
|
42
|
ACO Algorithms for the Quadratic Assignment Problem
– Stutzle, Dorigo
- 1999
|
|
41
|
HAS-SOP: Hybrid Ant System for the Sequential Ordering Problem
– Gambardella, Dorigo
- 1997
|
|
40
|
An ant approach to the flowshop problem
– Stützle
- 1998
|
|
39
|
Configuration space analysis of traveling salesman problems
– Kirkpatrick, Toulouse
- 1985
|
|
37
|
Models for Iterative Global Optimization
– Boese
- 1996
|
|
28
|
A New Rank Based Version of the Ant System --- A Computational Study
– Bullnheimer, Hartl, et al.
- 1997
|
|
25
|
From Natural to Artificial Swarm Intelligence
– Bonabeau, Dorigo, et al.
- 1999
|
|
20
|
Results of the first international contest on evolutionary optimisation (1st iceo
– Bersini, Dorigo, et al.
- 1996
|
|
19
|
Ant algorithms for distributed discrete optimization
– Dorigo, Caro, et al.
- 1999
|
|
15
|
Repair and Brood Selection in the Traveling Salesman Problem
– Walters
- 1998
|
|
13
|
Adaptive approach heuristics for the generalized assignment problem
– Lourenco, Serra
- 1998
|
|
11
|
Combinatorial Optimization by Iterative Partial Transcription
– Mobius, Freisleben, et al.
- 1999
|
|
11
|
ant system and local search for combinatorial optimization problems
– --MIN
- 1999
|
|
