Economics at your fingertips  

A new benchmark optimization problem of adaptable difficulty: theoretical considerations and practical testing

D. K. Karpouzos () and K. L. Katsifarakis ()
Additional contact information
D. K. Karpouzos: Aristotle University of Thessaloniki
K. L. Katsifarakis: Aristotle University of Thessaloniki

Operational Research, 2021, vol. 21, issue 1, No 8, 250 pages

Abstract: Abstract In this paper, we present a new benchmark problem for testing both local and global optimization techniques. This problem is based on ideas from groundwater hydraulics and simple Euclidian geometry and has the following attractive features: (a) known values of the infinite global optima, which can be classified in a restricted number of sets, with known location in the search space (b) simple form and (c) quick computation of objective function values. Moreover, the number of local optima sets, their location in the search space and thus the respective values of the objective function can be easily determined by the user, without affecting the global optimum value. In this way, the difficulty of finding the global optimum can be changed from quite small to almost insurmountable, as demonstrated by applying five widely used optimization methods, namely genetic algorithms, sequential quadratic programming, simulated annealing, Knitro and branch and bound. Moreover, some observations on the different behavior of optimization methods are discussed.

Keywords: Optimization; Benchmark problem; Adaptable difficulty; Genetic algorithms; Sequential quadratic programming; Simulated annealing; Knitro; Branch and bound (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from
https://www.springer ... search/journal/12351

DOI: 10.1007/s12351-019-00462-8

Access Statistics for this article

Operational Research is currently edited by Nikolaos F. Matsatsinis, John Psarras and Constantin Zopounidis

More articles in Operational Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

Page updated 2021-03-13
Handle: RePEc:spr:operea:v:21:y:2021:i:1:d:10.1007_s12351-019-00462-8