scholarly journals Minimum common string partition: on solving large-scale problem instances

2018 ◽  
Vol 27 (1) ◽  
pp. 91-111 ◽  
Author(s):  
Christian Blum

2015 ◽  
Vol 25 (3) ◽  
pp. 361-378 ◽  
Author(s):  
Miroslav Maric ◽  
Zorica Stanimirovic ◽  
Nikola Milenkovic ◽  
Aleksandar Djenic

In this study, we consider a variant of the Bilevel Uncapacitated Facility Location Problem (BLUFLP), in which the clients choose suppliers based on their own preferences. We propose and compare three metaheuristic approaches for solving this problem: Particle Swarm Optimization (PSO), Simulated Annealing (SA), and a combination of Reduced and Basic Variable Neighborhood Search Method (VNS). We used the representation of solutions and objective function calculation that are adequate for all three proposed methods. Additional strategy is implemented in order to provide significant time savings when evaluating small changes of solution's code in improvement parts. Constructive elements of each of the proposed algorithms are adapted to the problem under consideration. The results of broad computational tests on modified problem instances from the literature show good performance of all three proposed methods, even on large problem dimensions. However, the obtained results indicate that the proposed VNS-based has significantly better performance compared to SA and PSO approaches, especially when solving large-scale problem instances. Computational experiments on large scale benchmarks demonstrate that the VNS-based method is fast, competitive, and able to find high-quality solutions, even for large-scale problem instances with up to 2000 clients and 2000 potential facilities within reasonable CPU times.



Geophysics ◽  
2008 ◽  
Vol 73 (4) ◽  
pp. A23-A26 ◽  
Author(s):  
Gilles Hennenfent ◽  
Ewout van den Berg ◽  
Michael P. Friedlander ◽  
Felix J. Herrmann

Geophysical inverse problems typically involve a trade-off between data misfit and some prior model. Pareto curves trace the optimal trade-off between these two competing aims. These curves are used commonly in problems with two-norm priors in which they are plotted on a log-log scale and are known as L-curves. For other priors, such as the sparsity-promoting one-norm prior, Pareto curves remain relatively unexplored. We show how these curves lead to new insights into one-norm regularization. First, we confirm theoretical properties of smoothness and convexity of these curves from a stylized and a geophysical example. Second, we exploit these crucial properties to approximate the Pareto curve for a large-scale problem. Third, we show how Pareto curves provide an objective criterion to gauge how different one-norm solvers advance toward the solution.



1943 ◽  
Vol 37 (1) ◽  
pp. 30-45 ◽  
Author(s):  
Robert R. Wilson

A large-scale problem for the principal belligerents in the present war is that of the treatment of civilians of enemy nationality in their respective jurisdictions. Measured in terms of the number of human beings involved, national safety considerations, and the possibly unfortunate effect at home of mishandling it, the problem assumes far-reaching importance. There is need for clear law as well as positive action. There is need for perspective. In relation to international law, the distinctiveness of the classification of “civilian alien enemy,” past effort looking to the construction of internationally binding rules prescribing treatment, and practice in the current war, merit attention.



Author(s):  
R.B. Nairn ◽  
K.J. MacIntosh ◽  
M. O. Hayes ◽  
G. Nai ◽  
S.L. Anthonio ◽  
...  




2021 ◽  
Author(s):  
Saivipulteja Elagandula ◽  
Laxmi Poudel ◽  
Wenchao Zhou ◽  
Zhenghui Sha

Abstract This paper presents a decentralized approach based on a simple set of rules to carry out multi-robot cooperative 3D printing. Cooperative 3D printing is a novel approach to 3D printing that uses multiple mobile 3D printing robots to print a large part by dividing and assigning the part to multiple robots in parallel using the concept of chunk-based printing. The results obtained using the decentralized approach are then compared with those obtained from the centralized approach. Two case studies were performed to evaluate the performance of both approaches using makespan as the evaluation criterion. The first case is a small-scale problem with four printing robots and 20 chunks, whereas the second case study is a large-scale problem with ten printing robots and 200 chunks. The result shows that the centralized approach provides a better solution compared to the decentralized approach in both cases in terms of makespan. However, the gap between the solutions seems to shrink with the scale of the problem. While further study is required to verify this conclusion, the decrease in this gap indicates that the decentralized approach might compare favorably over the centralized approach for a large-scale problem in manufacturing using multiple mobile 3D printing robots. Additionally, the runtime for the large-scale problem (Case II) increases by 27-fold compared to the small-scale problem (Case I) for the centralized approach, whereas it only increased by less than 2-fold for the decentralized approach.



2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Igor Litvinchev ◽  
Fernando Lopez-Irarragorri ◽  
Nancy Maribel Arratia-Martínez ◽  
José Antonio Marmolejo

We address the portfolio selection of social projects in public organizations considering interdependencies (synergies) affecting project funds requirements and tasks. A mixed integer linear programming model is proposed incorporating the most relevant aspects of the problem found in the literature. The model supports both complete (all or nothing) and partial (a certain amount from a given interval of funding) resource allocation policies. Numerical results for large-scale problem instances are presented.



Author(s):  
Thomas W. Malone ◽  
Jeffrey V. Nickerson ◽  
Robert Laubacher ◽  
Laur Hesse Fisher ◽  
Yue Han ◽  
...  


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