A distance-based selection of parents in genetic algorithms
Metaheuristics
An ant algorithm for the single row layout problem in flexible manufacturing systems
Computers and Operations Research
A tabu search algorithm for the quadratic assignment problem
Computational Optimization and Applications
A study of ACO capabilities for solving the maximum clique problem
Journal of Heuristics
A Hybrid Metaheuristic for the Quadratic Assignment Problem
Computational Optimization and Applications
A fast hybrid genetic algorithm for the quadratic assignment problem
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Broadcast filtering-aware task assignment techniques for low-power MPSoCs
MEDEA '07 Proceedings of the 2007 workshop on MEmory performance: DEaling with Applications, systems and architecture
Computational Optimization and Applications
An ant algorithm for balanced job scheduling in grids
Future Generation Computer Systems
Robotics and Computer-Integrated Manufacturing
The single-finger keyboard layout problem
Computers and Operations Research
A New Ant Colony Optimization Algorithm with an Escape Mechanism for Scheduling Problems
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Ruin and recreate principle based approach for the quadratic assignment problem
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Variable neighborhood search with permutation distance for QAP
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
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The paper proposes, compares and analyses different memory- based meta-heuristics for the quadratic assignment problem (QAP). Two of these methods (FANT and GDH) are new while two others (HAS-QAP and GTSH) are among the best for structured QAP instances. These methods are based on ant systems and genetic algorithms and they are presented under a unified general scheme, called adaptive memory programming (AMP). However, they use different types of memory and different improving procedures. Two new memoryless methods (VNS-QAP and RVNS-QAP) based on variable neighbourhood search are also proposed and compared with adaptive memory procedures.