Solving a Continuous Multifacility Location Problem by DC Algorithms
Sponsor
Research of this author was partly supported by the USA National Science Foundation (Directorate for Mathematical and Physical Sciences) [grant number DMS-1512846], [grant number DMS-1808978] and [grant number DMS-1716057], by the USA Air Force Office of Scientific Research [grant number #15RT04], and by Australian Research Council [grant number DP-190100555].
Published In
Optimization Methods & Software
Document Type
Citation
Publication Date
1-2-2022
Abstract
The paper presents a new approach to solve multifacility location problems, which is based on mixed integer programming and algorithms for minimizing differences of convex (DC) functions. The main challenges for solving the multifacility location problems under consideration come from their intrinsic discrete, nonconvex, and nondifferentiable nature. We provide a reformulation of these problems as those of continuous optimization and then develop a new DC type algorithm for their solutions involving Nesterov's smoothing. The proposed algorithm is computationally implemented via MATLAB numerical tests on both artificial and real data sets.
Rights
© 2020 Informa UK Limited, trading as Taylor & Francis Group
Locate the Document
DOI
10.1080/10556788.2020.1771335
Persistent Identifier
https://archives.pdx.edu/ds/psu/39729
Publisher
Informa UK Limited
Citation Details
Bajaj, A., Mordukhovich, B. S., Nam, N. M., & Tran, T. (2020). Solving a continuous multifacility location problem by DC algorithms. Optimization Methods and Software, 37(1), 338–360.