A connectionist approach to the quadratic assignment problem
Computers and Operations Research - Special issue on neural networks and operations research
Extensions of a tabu search adaptation to the quadratic assignment problem
Computers and Operations Research - Special issue: heuristic, genetic and tabu search
A genetic approach to the quadratic assignment problem
Computers and Operations Research - Special issue on genetic algorithms
ACO algorithms for the quadratic assignment problem
New ideas in optimization
Computers and Industrial Engineering
Computational Optimization and Applications
A greedy genetic algorithm for the quadratic assignment problem
Computers and Operations Research
On the landscape ruggedness of the quadratic assignment problem
Theoretical Computer Science
Parallel ant colonies for the quadratic assignment problem
Future Generation Computer Systems - Special issue on bio-impaired solutions to parallel processing problems
Assignment and Matching Problems: Solution Methods with FORTRAN-Programs
Assignment and Matching Problems: Solution Methods with FORTRAN-Programs
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
QAPLIB – A Quadratic Assignment ProblemLibrary
Journal of Global Optimization
Extensive Testing of a Hybrid Genetic Algorithm for Solving Quadratic Assignment Problems
Computational Optimization and Applications
The Ant System Applied to the Quadratic Assignment Problem
IEEE Transactions on Knowledge and Data Engineering
Adaptive memories for the Quadratic Assignment Problems
Adaptive memories for the Quadratic Assignment Problems
Fitness landscape analysis and memetic algorithms for the quadratic assignment problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multistart tabu search and diversification strategies for the quadratic assignment problem
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Biogeography-based optimization combined with evolutionary strategy and immigration refusal
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Expert Systems with Applications: An International Journal
Learning hybridization strategies in evolutionary algorithms
Intelligent Data Analysis
International Journal of Applied Evolutionary Computation
Path Relinking with Multi-Start Tabu Search for the Quadratic Assignment Problem
International Journal of Swarm Intelligence Research
Applied Soft Computing
A new hybrid metaheuristic for medical data classification
International Journal of Metaheuristics
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The quadratic assignment problem (QAP) is known to be NP-hard. We propose a hybrid metaheuristic called ANGEL to solve QAP. ANGEL combines the ant colony optimization (ACO), the genetic algorithm (GA) and a local search method (LS). There are two major phases in ANGEL, namely ACO phase and GA phase. Instead of starting from a population that consists of randomly generated chromosomes, GA has an initial population constructed by ACO in order to provide a good start. Pheromone acts as a feedback mechanism from GA phase to ACO phase. When GA phase reaches the termination criterion, control is transferred back to ACO phase. Then ACO utilizes pheromone updated by GA phase to explore solution space and produces a promising population for the next run of GA phase. The local search method is applied to improve the solutions obtained by ACO and GA. We also propose a new concept called the eugenic strategy intended to guide the genetic algorithm to evolve toward a better direction. We report the results of a comprehensive testing of ANGEL in solving QAP. Over a hundred instances of QAP benchmarks were tested and the results show that ANGEL is able to obtain the optimal solution with a high success rate of 90%.