Paper Title :GRASP and Statistical Bounds for Heuristic Solutions to Combinatorial Problems
Author :Mengjie Han, Kenneth Carling
Article Citation :Mengjie Han ,Kenneth Carling ,
(2019 ) " GRASP and Statistical Bounds for Heuristic Solutions to Combinatorial Problems " ,
International Journal of Management and Applied Science (IJMAS) ,
pp. 113-119,
Volume-5,Issue-8
Abstract : The quality of a heuristic solution to a NP-hard combinatorial problem is hard to assess. A few studies have
advocated and tested statistical bounds as a method for assessment. These studies indicate that statistical bounds are superior
to the more widely known and used deterministic bounds. However, the previous studies have been limited to a few
heuristics and combinatorial problems and, hence, the general performance of statistical bounds in combinatorial
optimization remains an open question. This work complements the existing literature on statistical bounds by testing them
on the metaheuristic Greedy Randomized Adaptive Search Procedures (GRASP) and four combinatorial problems. Our
findings confirm previous results that statistical bounds are reliable for the p-median problem, while we note that they also
seem reliable for the set covering problem. For the quadratic assignment problem, the statistical bounds have previously
been found reliable when obtained from the Genetic algorithm whereas in this work they have been found less reliable.
Finally, we provide statistical bounds to four 2-path network design problem instances for which the optimum is currently
unknown.
Key Words- Combinatorial Problems, GRASP, Statistical Bounds, Statistical Optimum Estimation Techniques
Type : Research paper
Published : Volume-5,Issue-8
Copyright: © Institute of Research and Journals
| |
 |
| |
 |
PDF |
| |
Viewed - 61 |
| |
Published on 2019-11-04 |
|
