A Modified Particle Swarm Optimization Algorithm for Location Problem
URI (for links/citations):https://iopscience.iop.org/article/10.1088/1757-899X/537/4/042060/pdf
Osinuga, I. A.
Bolarinwa, A. A.
Казаковцев, Л. А.
Институт управления бизнес-процессами и экономики
Кафедра экономики и информационных технологий менеджмента
Journal Name:IOP Conference Series: Materials Science and Engineering
Journal Quartile in Scopus:без квартиля
Journal Quartile in Web of Science:без квартиля
Bibliographic Citation:Osinuga, I. A. A Modified Particle Swarm Optimization Algorithm for Location Problem [Текст] / I. A. Osinuga, A. A. Bolarinwa, Л. А. Казаковцев // IOP Conference Series: Materials Science and Engineering. — 2019. — Т. 537 (№ 4). — С. 042060
In the Weber location problem which was proposed for optimal location of industrial enterprises, the aim is to find the location of a point such that the sum of weighted distance between this point and a finite number of existing points is minimized. This popular model is widely used for optimal location of equipment and in many sophisticated models of cluster analysis such as detecting homogeneous production batches made from a single production batch of raw materials. The well-known iterative Weiszfeld does not converge efficiently to the optimal solution when the solution either coincides or nearly coincides with one of the demands point which is not the optimum. We propose a modified Particle Swarm Optimization (PSO) algorithm. The velocity update of thePSO is modified to enlarge the search space and enhance the global search ability. The preliminary results of these algorithms are analyzed and compared.