Evaluating and Tuning n-fold Integer Programming
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10403776" target="_blank" >RIV/00216208:11320/19:10403776 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21240/19:00333753
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=J6g0RJ51c1" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=J6g0RJ51c1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3330137" target="_blank" >10.1145/3330137</a>
Alternative languages
Result language
angličtina
Original language name
Evaluating and Tuning n-fold Integer Programming
Original language description
In recent years, algorithmic breakthroughs in stringology, computational social choice, scheduling, and so on, were achieved by applying the theory of so-called n-fold integer programming. An n-fold integer program (IP) has a highly uniform block structured constraint matrix. Hemmecke, Onn, and Romanchuk [Math. Program., 2013] showed an algorithm with runtime ΔO(rst + r2s) n3, where Δ is the largest coefficient, r,s, and t are dimensions of blocks of the constraint matrix and n is the total dimension of the IP; thus, an algorithm efficient if the blocks are of small size and with small coefficients. The algorithm works by iteratively improving a feasible solution with augmenting steps, and n-fold IPs have the special property that augmenting steps are guaranteed to exist in a not-too-large neighborhood. However, this algorithm has never been implemented and evaluated. We have implemented the algorithm and learned the following along the way. The original algorithm is practically unusable, but we discover a series of improvements that make its evaluation possible. Crucially, we observe that a certain constant in the algorithm can be treated as a tuning parameter, which yields an efficient heuristic (essentially searching in a smaller-than-guaranteed neighborhood). Furthermore, the algorithm uses an overly expensive strategy to find a "best" step, while finding only an "approximately best" step is much cheaper, yet sufficient for quick convergence. Using this insight, we improve the asymptotic dependence on n from n3 to n2 log n. Finally, we tested the behavior of the algorithm with various values of the tuning parameter and different strategies of finding improving steps. First, we show that decreasing the tuning parameter initially leads to an increased number of iterations needed for convergence and eventually to getting stuck in local optima, as expected. However, surprisingly small values of the parameter already exhibit good behavior while significantly lowering the time the algorithm spends per single iteration. Second, our new strategy for finding "approximately best" steps wildly outperforms the original construction.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA17-09142S" target="_blank" >GA17-09142S: Modern algorithms: New challenges of complex data sets</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Experimental Algorithmics
ISSN
1084-6654
e-ISSN
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Volume of the periodical
2019
Issue of the periodical within the volume
24
Country of publishing house
US - UNITED STATES
Number of pages
22
Pages from-to
1-22
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85069915485