Convergence of an annealing algorithm
Mathematical Programming: Series A and B
Cooling schedules for optimal annealing
Mathematics of Operations Research
Simulated annealing: theory and applications
Simulated annealing: theory and applications
Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
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Systems & Control Letters
Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
Annals of Operations Research - Special issue on Tabu search
P-Complete Approximation Problems
Journal of the ACM (JACM)
QAPLIB – A Quadratic Assignment ProblemLibrary
Journal of Global Optimization
Image and Vision Computing
Computers and Operations Research
On topology reconfiguration for defect-tolerant NoC-based homogeneous manycore systems
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Effective formulation reductions for the quadratic assignment problem
Computers and Operations Research
Chemical-reaction-inspired metaheuristic for optimization
IEEE Transactions on Evolutionary Computation
Design of self tuning fuzzy controllers for nonlinear systems
Expert Systems with Applications: An International Journal
Three improved variants of simulated annealing for optimising dorm room assignments
International Journal of Intelligent Information and Database Systems
Robotics and Computer-Integrated Manufacturing
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
Operations Research Letters
Thermal-constrained task allocation for interconnect energy reduction in 3-D homogeneous MPSoCs
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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The quadratic assignment problem (QAP) is one of the well-known combinatorial optimization problems and is known for its various applications. In this paper, we propose a modified simulated annealing algorithm for the QAP - M-SA-QAP. The novelty of the proposed algorithm is an advanced formula of calculation of the initial and final temperatures, as well as an original cooling schedule with oscillation, i.e., periodical decreasing and increasing of the temperature. In addition, in order to improve the results obtained, the simulated annealing algorithm is combined with a tabu search approach based algorithm. We tested our algorithm on a number of instances from the library of the QAP instances - QAPLIB. The results obtained from the experiments show that the proposed algorithm appears to be superior to earlier versions of the simulated annealing for the QAP. The power of M-SA-QAP is also corroborated by the fact that the new best known solution was found for the one of the largest QAP instances - THO150.