The Unicost Set Covering Problem is a basic mathematical problem with which many problems faced by businesses in real life can be modeled. In the problem, it is aimed to select the least number of clusters to contain all of the observations in the data set. In the solution of the problem expressed in the form of integer programming, various iterative approaches are used due to the inadequacy of classical and exact methods. One of these approaches is local search algorithms. Within the scope of the study, a local search algorithm suitable for the problem's own structure and based on adaptive weighting of the observations is proposed. For the variables created using the adaptive structure, the outputs obtained during the optimization process are considered as input parameters. In this way, it is aimed to make a smarter local search approach. The proposed adaptive method is used in solving the examples of unicost set covering problem and its performance is compared with other adaptive methods in the literature. By examining the results, the efficiency of the developed method is revealed.
Primary Language | Turkish |
---|---|
Subjects | Business Administration |
Journal Section | Research Articles |
Authors | |
Publication Date | November 20, 2021 |
Submission Date | February 5, 2021 |
Published in Issue | Year 2021 Volume: 12 Issue: 32 |