Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
A greedy genetic algorithm for the quadratic assignment problem
Computers and Operations Research
QAPLIB – A Quadratic Assignment ProblemLibrary
Journal of Global Optimization
Journal of Global Optimization
A survey of very large-scale neighborhood search techniques
Discrete Applied Mathematics
A genetic algorithm approach for regrouping service sites
Computers and Operations Research
Computers and Operations Research
Journal of Global Optimization
A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem
Computers and Operations Research
Using solution properties within an enumerative search to solve a sports league scheduling problem
Discrete Applied Mathematics
A discrete differential evolution algorithm for the permutation flowshop scheduling problem
Computers and Industrial Engineering
A new iterated fast local search heuristic for solving QAP formulation in facility layout design
Robotics and Computer-Integrated Manufacturing
A bio-inspired crime simulation model
Decision Support Systems
Paper: Robust taboo search for the quadratic assignment problem
Parallel Computing
Honey Bees Mating Optimization algorithm for financial classification problems
Applied Soft Computing
Effective formulation reductions for the quadratic assignment problem
Computers and Operations Research
Self Controlling Tabu Search algorithm for the Quadratic Assignment Problem
Computers and Industrial Engineering
Information Sciences: an International Journal
Information Sciences: an International Journal
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Solving credit card fraud detection problem by the new metaheuristics migrating birds optimization
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advences in computational intelligence - Volume Part II
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We propose a new nature inspired metaheuristic approach based on the V flight formation of the migrating birds which is proven to be an effective formation in energy saving. Its performance is tested on quadratic assignment problem instances arising from a real life problem and very good results are obtained. The quality of the solutions we report are better than simulated annealing, tabu search, genetic algorithm, scatter search, particle swarm optimization, differential evolution and guided evolutionary simulated annealing approaches. The proposed method is also tested on a number of benchmark problems obtained from the QAPLIB and in most cases it was able to obtain the best known solutions. These results indicate that our new metaheuristic approach could be an important player in metaheuristic based optimization.