Algorithms for the continuous nonlinear resource allocation problem - New implementations and numerical studies
Artikel i vetenskaplig tidskrift, 2015

Patriksson (2008) provided a then up-to-date survey on the continuous, separable, differentiable and convex resource allocation problem with a single resource constraint. Since the publication of that paper the interest in the problem has grown: several new applications have arisen where the problem at hand constitutes a subproblem, and several new algorithms have been developed for its efficient solution. This paper therefore serves three purposes. First, it provides an up-to-date extension of the survey of the literature of the field, complementing the survey in Patriksson (2008) with more then 20 books and articles. Second, it contributes improvements of some of these algorithms, in particular with an improvement of the pegging (that is, variable fixing) process in the relaxation algorithm, and an improved means to evaluate subsolutions. Third, it numerically evaluates several relaxation (primal) and breakpoint (dual) algorithms, incorporating a variety of pegging strategies, as well as a quasi-Newton method. Our conclusion is that our modification of the relaxation algorithm performs the best. At least for problem sizes up to 30 million variables the practical time complexity for the breakpoint and relaxation algorithms is linear.

Numerical analysis

Resource allocation

Lagrangian duality

Applications

Convex optimization

Författare

Michael Patriksson

Chalmers, Matematiska vetenskaper, Matematik

Göteborgs universitet

Christoffer Strömberg

European Journal of Operational Research

0377-2217 (ISSN)

Vol. 243 703-722

Drivkrafter

Hållbar utveckling

Innovation och entreprenörskap

Styrkeområden

Transport

Produktion

Ämneskategorier

Beräkningsmatematik

Fundament

Grundläggande vetenskaper

DOI

10.1016/j.ejor.2015.01.029