ORCID Profile
0000-0002-6120-8484
Current Organisations
Monash University - Caulfield Campus
,
Monash University
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Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/11802839_50
Publisher: Springer International Publishing
Date: 2018
Publisher: Pleiades Publishing Ltd
Date: 2011
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Date: 04-2013
Abstract: We consider the feasibility problem OPP (orthogonal packing problem) in higher-dimensional orthogonal packing: given a set of d-dimensional (d ≥ 2) rectangular items, decide whether all of them can be orthogonally packed in the given rectangular container without rotation. The one-dimensional (1D) “bar” LP relaxation of OPP reduces the latter to a 1D cutting-stock problem where the packing of each stock bar represents a possible 1D stitch through an OPP layout. The dual multipliers of the LP provide us with another kind of powerful bounding information (conservative scales). We investigate how the set of possible 1D packings can be tightened using the overlapping information of item projections on the axes, with the goal to tighten the relaxation. We integrate the bar relaxation into an interval-graph algorithm for OPP, which operates on such overlapping relations. Numerical results on 2D and 3D instances demonstrate the efficiency of tightening leading to a speedup and stabilization of the algorithm.
Publisher: Institution of Engineering and Technology
Date: 2012
DOI: 10.1049/CP.2012.2164
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Date: 02-2007
Abstract: The primary objective in cutting and packing problems is trim loss or material input minimization (in stock cutting) or value maximization (in knapsack-type problems). However, in real-life production we usually have many other objectives (costs) and constraints. Probably the most complex auxiliary criteria in one-dimensional stock cutting are the number of different cutting patterns (setups) and the maximum number of open stacks during the cutting process. There are applications where the number of stacks is restricted to two. We design a sequential heuristic to minimize material input and show its high effectiveness for this purpose. Then we extend it to restrict the number of open stacks to any given limit. Then, the heuristic is simplified and integrated into a setup-minimization approach in order to combine setup and open-stacks minimization. To get a smaller number of open stacks, we may split up the problem into several parts of smaller sizes. Different solutions are evaluated in relation to the multiple objectives using the Pareto criterion.
Publisher: IEEE
Date: 10-2012
Publisher: Wiley
Date: 11-2009
Publisher: Springer International Publishing
Date: 2014
Publisher: Springer Science and Business Media LLC
Date: 10-12-2013
Publisher: Springer Science and Business Media LLC
Date: 06-2023
DOI: 10.1007/S10601-023-09344-5
Abstract: Decision systems for solving real-world combinatorial problems must be able to report infeasibility in such a way that users can understand the reasons behind it, and determine how to modify the problem to restore feasibility. Current methods mainly focus on reporting one or more subsets of the problem constraints that cause infeasibility. Methods that also show users how to restore feasibility tend to be less flexible and/or problem-dependent. We describe a problem-independent approach to feasibility restoration that combines existing techniques from the literature in novel ways to yield meaningful, useful, practical, and flexible user support. We evaluated the resulting framework on three real-world applications and conducted a qualitative expert user study with participants from different application domains.
Publisher: Elsevier BV
Date: 09-2002
Publisher: IEEE
Date: 10-2013
Publisher: Springer International Publishing
Date: 2017
Publisher: Springer International Publishing
Date: 2016
Publisher: International Joint Conferences on Artificial Intelligence Organization
Date: 08-2017
Abstract: We show how recently-defined abstract models of the Branch-and-Bound algorithm can be used to obtain information on how the nodes are distributed in B& B search trees. This can be directly exploited in the form of probabilities in a s ling algorithm given by Knuth that estimates the size of a search tree. This method reduces the offline estimation error by a factor of two on search trees from Mixed-Integer Programming instances.
Publisher: Elsevier BV
Date: 05-2006
Publisher: Springer Science and Business Media LLC
Date: 14-01-2020
Publisher: Informa UK Limited
Date: 06-2008
Publisher: Elsevier BV
Date: 10-2012
Publisher: Informa UK Limited
Date: 12-2001
No related grants have been discovered for Gleb Belov.