scholarly journals Pricing-based primal and dual bounds for selected packing problems

4OR ◽  
2020 ◽  
Author(s):  
Andrea Pizzuti
Author(s):  
Carleton Coffrin ◽  
Hassan L. Hijazi ◽  
Karsten Lehmann ◽  
Pascal Van Hentenryck

2020 ◽  
Vol 58 (6) ◽  
pp. 3709-3733
Author(s):  
Chunxi Jiao ◽  
Reiichiro Kawai

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Darina Dvinskikh ◽  
Alexander Gasnikov

Abstract We introduce primal and dual stochastic gradient oracle methods for decentralized convex optimization problems. Both for primal and dual oracles, the proposed methods are optimal in terms of the number of communication steps. However, for all classes of the objective, the optimality in terms of the number of oracle calls per node takes place only up to a logarithmic factor and the notion of smoothness. By using mini-batching technique, we show that the proposed methods with stochastic oracle can be additionally parallelized at each node. The considered algorithms can be applied to many data science problems and inverse problems.


Author(s):  
Klaus Jansen ◽  
Kim-Manuel Klein ◽  
Marten Maack ◽  
Malin Rau

AbstractInteger linear programs of configurations, or configuration IPs, are a classical tool in the design of algorithms for scheduling and packing problems where a set of items has to be placed in multiple target locations. Herein, a configuration describes a possible placement on one of the target locations, and the IP is used to choose suitable configurations covering the items. We give an augmented IP formulation, which we call the module configuration IP. It can be described within the framework of n-fold integer programming and, therefore, be solved efficiently. As an application, we consider scheduling problems with setup times in which a set of jobs has to be scheduled on a set of identical machines with the objective of minimizing the makespan. For instance, we investigate the case that jobs can be split and scheduled on multiple machines. However, before a part of a job can be processed, an uninterrupted setup depending on the job has to be paid. For both of the variants that jobs can be executed in parallel or not, we obtain an efficient polynomial time approximation scheme (EPTAS) of running time $$f(1/\varepsilon )\cdot \mathrm {poly}(|I|)$$ f ( 1 / ε ) · poly ( | I | ) . Previously, only constant factor approximations of 5/3 and $$4/3 + \varepsilon $$ 4 / 3 + ε , respectively, were known. Furthermore, we present an EPTAS for a problem where classes of (non-splittable) jobs are given, and a setup has to be paid for each class of jobs being executed on one machine.


2010 ◽  
Vol 92 (2) ◽  
pp. 211-229 ◽  
Author(s):  
Christoph Brune ◽  
Alex Sawatzky ◽  
Martin Burger
Keyword(s):  

Author(s):  
Hong Dong ◽  
Georges M. Fadel ◽  
Vincent Y. Blouin

In this paper, some new developments to the packing optimization method based on the rubber band analogy are presented. This method solves packing problems by simulating the physical movements of a set of objects wrapped by a rubber band in the case of two-dimensional problems or by a rubber balloon in the case of three-dimensional problems. The objects are subjected to elastic forces applied by the rubber band to their vertices as well as reaction forces when contacts between objects occur. Based on these forces, objects translate or rotate until maximum compactness is reached. To improve the compactness further, the method is enhanced by adding two new operators: volume relaxation and temporary retraction. These two operators allow temporary volume (elastic energy) increase to get potentially better packing results. The method is implemented and applied for three-dimensional arbitrary shape objects.


2014 ◽  
Vol 111 ◽  
pp. 654-662 ◽  
Author(s):  
Teodor Gabriel Crainic ◽  
Luca Gobbato ◽  
Guido Perboli ◽  
Walter Rei ◽  
Jean-Paul Watson ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document