Sergienko I.V., Shylo V.P.
Kernel technology to solve discrete optimization problems

The kernel technology is proposed to solve discrete optimization problems. It forms solution kernel and allows efficient stochastic perturbations of this solution in iterative schemes. Comparative analysis of the two versions of the new algorithm for the quadratic assignment problem (with and without kernel allocation technology) and modern algorithms demonstrated the efficiency of this technology in terms of speed and solution quality. The kernel technology can be easily incorporated into the available algorithms. © 2017, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords: Boolean quadratic programming problem UBQP, comparative study of algorithms, computing experiment, job scheduling problem JSP, kernel technology, problem of maximum weighted cut of a graph WMaxCut, quadratic assignment problem QAP, traveling salesman problem TSP, Combinatorial optimization, Iterative methods, Optimization, Quadratic programming, Stochastic systems, Traveling salesman problem, Comparative studies, Computing Experiments, Job scheduling problem, problem of maximum weighted cut of a graph WMaxCut, Quadratic assignment problems, Quadratic programming problems, Problem solving

Cite:
Sergienko I.V., Shylo V.P. (2017). Kernel technology to solve discrete optimization problems. Cybernetics and Systems Analysis, 53 (6), 73-83. doi: https://doi.org/10.1007/s10559-017-9990-y http://jnas.nbuv.gov.ua/article/UJRN-0000782702 [In Russian].