Library

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
Source
Years
Language
  • 1
    Publication Date: 2020-08-05
    Description: We consider reoptimization (i.e. the solution of a problem based on information available from solving a similar problem) for branch-and-bound algorithms and propose a generic framework to construct a reoptimizing branch-and-bound algorithm. We apply this to an elevator scheduling algorithm solving similar subproblems to generate columns using branch-and-bound. Our results indicate that reoptimization techniques can substantially reduce the running times of the overall algorithm.
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2020-08-05
    Description: Recently, there have been many successful applications of optimization algorithms that solve a sequence of quite similar mixed-integer programs (MIPs) as subproblems. Traditionally, each problem in the sequence is solved from scratch. In this paper we consider reoptimization techniques that try to benefit from information obtained by solving previous problems of the sequence. We focus on the case that subsequent MIPs differ only in the objective function or that the feasible region is reduced. We propose extensions of the very complex branch-and-bound algorithms employed by general MIP solvers based on the idea to ``warmstart'' using the final search frontier of the preceding solver run. We extend the academic MIP solver SCIP by these techniques to obtain a reoptimizing branch-and-bound solver and report computational results which show the effectiveness of the approach.
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 3
    Publication Date: 2020-08-05
    Description: Recently, there have been many successful applications of optimization algorithms that solve a sequence of quite similar mixed-integer programs (MIPs) as subproblems. Traditionally, each problem in the sequence is solved from scratch. In this paper we consider reoptimization techniques that try to benefit from information obtained by solving previous problems of the sequence. We focus on the case that subsequent MIPs differ only in the objective function or that the feasible region is reduced. We propose extensions of the very complex branch-and-bound algorithms employed by general MIP solvers based on the idea to ``warmstart'' using the final search frontier of the preceding solver run. We extend the academic MIP solver SCIP by these techniques to obtain a reoptimizing branch-and-bound solver and report computational results which show the effectiveness of the approach.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 4
    Publication Date: 2021-01-22
    Description: The SCIP Optimization Suite is a software toolbox for generating and solving various classes of mathematical optimization problems. Its major components are the modeling language ZIMPL, the linear programming solver SoPlex, the constraint integer programming framework and mixed-integer linear and nonlinear programming solver SCIP, the UG framework for parallelization of branch-and-bound-based solvers, and the generic branch-cut-and-price solver GCG. It has been used in many applications from both academia and industry and is one of the leading non-commercial solvers. This paper highlights the new features of version 3.2 of the SCIP Optimization Suite. Version 3.2 was released in July 2015. This release comes with new presolving steps, primal heuristics, and branching rules within SCIP. In addition, version 3.2 includes a reoptimization feature and improved handling of quadratic constraints and special ordered sets. SoPlex can now solve LPs exactly over the rational number and performance improvements have been achieved by exploiting sparsity in more situations. UG has been tested successfully on 80,000 cores. A major new feature of UG is the functionality to parallelize a customized SCIP solver. GCG has been enhanced with a new separator, new primal heuristics, and improved column management. Finally, new and improved extensions of SCIP are presented, namely solvers for multi-criteria optimization, Steiner tree problems, and mixed-integer semidefinite programs.
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 5
    Publication Date: 2020-08-05
    Description: Heutzutage ist eine Vielzahl der mehrstöckigen Gebäude mit Personenaufzugsgruppen ausgestattet. Uns wohl bekannt sind die sogenannten konventionellen Systeme. Bei diesen Systemen betätigt jeder ankommende Passagier eine der beiden Richtungstasten und teilt dem dahinterstehenden Steuerungsalgorithmus seine gewünschte Startetage und Fahrtrichtung mit. Betreten wird der zuerst auf der Startetage ankommende Aufzug mit gleicher Fahrtrichtung und ausreichend Kapazität. Die entsprechende Zieletage wird dem System erst nach dem Betreten der Fahrgastkabine mitgeteilt. Neben diesen konventionellen Systemen gibt es Aufzugsgruppen mit Zielrufsteuerung. Die Besonderheit eines zielrufgesteuerten Systems ist, dass ein ankommender Passagier bereits auf der Startetage seine gewünschte Zieletage angibt und eine Rückmeldung vom System erhält, welchen Aufzug er nutzen soll. Diese Zuweisung durch das System hat das Ziel, die Warte- und Reisezeiten der Passagiere zu minimieren. Ein wesentlicher Faktor bei der Berechnung warte- und reisezeitminimaler Fahrpläne ist das momentane Verkehrsmuster. Eine Einteilung der Verkehrsszenarien lässt sich am besten bei Bürogebäuden vornehmen. So ist es typisch für die Morgenstunden, dass jeder Passagier auf einer Zugangsebene seine Fahrt beginnt und alle Passagiere die gleiche Fahrtrichtung haben. Unter einer Zugangsebene ist z. B. der Haupteingang oder ein Parkdeck zu verstehen. Ein weiterer wesentlicher Punkt bei Zielrufsystemen ist die Art der Zuweisung der Passagiere durch das System. Zum einen gibt es unmittelbar zuweisende (UZ-) Systeme. In einem UZ-System wird nach jeder Ankunft eines Passagiers eine Momentaufnahme des momentanen Verkehrs erstellt und es findet eine Neuplanung und Zuweisung statt. Eine solche Momentaufnahme werden wir im späteren Verkauf als Schnappschussproblem bezeichnen. Jeder Passagier bekommt im Anschluss an die Lösung des Schnappschussproblems eine Mitteilung vom System, z. B. über ein Display, welchen Aufzug er benutzen soll. Zum anderen gibt es verzögert zuweisende (VZ-) Systeme. In diesen Systemen wird die Erstellung und Lösung eines Schnappschussproblems bis kurz vor Ankunft eines Aufzuges auf einer Etage verzögert. In einem VZ-System teilt das System allen wartenden Passagieren die geplanten Zieletagen des ankommenden Aufzugs mit. Jeder Passagier, der einen Ruf getätigt hat und zu einer dieser Zieletagen fahren will, kann jetzt diesen Aufzug betreten. Durch die Verzögerung muss im Vergleich zu einem UZ-System eine weitaus größere Menge von Passagieren zugewiesen werden. Dadurch kann der Lösungsprozess bedeutend aufwändiger werden. Vorteil eines VZ-Systems ist hingegen der größere Freiheitsgrad bei der Optimierung, da aufgrund der späten Zuweisung die weitere Verkehrsentwicklung mit einbezogen werden kann. VZ-Systeme sind aufgrund des größeren Freiheitsgrades interessant für die Praxis ist, wir uns demzufolge in dieser Arbeit mit einer effizienteren Lösung dieser Art von Schnappschussproblemen befassen. Es genügt dabei den Lösungsprozess eines Schnappschussproblems zu betrachten. Das Ziel ist eine Reduzierung der benötigten Rechenzeit. Unter Reoptimierung verstehen wir die Konstruktion zulässiger Spalten in den jeweiligen Iterationsrunden der Spaltengenerierung innerhalb eines Schnappschussproblems. Als eine Iterationsrunde bezeichnet wir einer Menge zulässiger Touren mit negativen reduzierten Kosten. Eine effiziente Reoptimierung zeichnet sich durch die Wiederverwendung und Aufbereitung von Informationen aus vorangegangenen Iterationsrunden desselben Schnappschussproblems aus. Zu den wichtigen Informationen gehört der konstruierte Suchbaum der vorherigen Iterationsrunde mit seinen ausgeloteten (abgeschnittenen) Blättern sowie konstruierten Touren bzw. Spalten, welche in der Iterationsrunde ihrer Konstruktion nicht zur Lösung des Teilproblems der Spaltengenerierung beitrugen. Eine solche Wiederverwendung und Aufbereitung von Informationen nennen wir Warmstart.
    Language: German
    Type: bachelorthesis , doc-type:bachelorThesis
    Format: application/pdf
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 6
    Publication Date: 2022-03-14
    Description: The analysis of infeasible subproblems plays an import role in solving mixed integer programs (MIPs) and is implemented in most major MIP solvers. There are two fundamentally different concepts to generate valid global constraints from infeasible subproblems. The first is to analyze the sequence of implications obtained by domain propagation that led to infeasibility. The result of the analysis is one or more sets of contradicting variable bounds from which so-called conflict constraints can be generated. This concept has its origin in solving satisfiability problems and is similarly used in constraint programming. The second concept is to analyze infeasible linear programming (LP) relaxations. The dual LP solution provides a set of multipliers that can be used to generate a single new globally valid linear constraint. The main contribution of this short paper is an empirical evaluation of two ways to combine both approaches. Experiments are carried out on general MIP instances from standard public test sets such as Miplib2010; the presented algorithms have been implemented within the non-commercial MIP solver SCIP. Moreover, we present a pool-based approach to manage conflicts which addresses the way a MIP solver traverses the search tree better than aging strategies known from SAT solving.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 7
    Publication Date: 2020-08-05
    Description: We consider the problem of pattern detection in large scale railway timetables. This problem arises in rolling stock optimization planning in order to identify invariant sections of the timetable for which a cyclic rotation plan is adequate. We propose a dual reduction technique which leads to an decomposition and enumeration method. Computational results for real world instances demonstrate that the method is able to produce optimal solutions as fast as standard MIP solvers.
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 8
    Publication Date: 2022-03-11
    Description: The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. This paper discusses enhancements and extensions contained in version 8.0 of the SCIP Optimization Suite. Major updates in SCIP include improvements in symmetry handling and decomposition algorithms, new cutting planes, a new plugin type for cut selection, and a complete rework of the way nonlinear constraints are handled. Additionally, SCIP 8.0 now supports interfaces for Julia as well as Matlab. Further, UG now includes a unified framework to parallelize all solvers, a utility to analyze computational experiments has been added to GCG, dual solutions can be postsolved by PaPILO, new heuristics and presolving methods were added to SCIP-SDP, and additional problem classes and major performance improvements are available in SCIP-Jack.
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 9
    Publication Date: 2022-03-11
    Description: In this paper, we present a new, optimization-based method to exhibit cyclic behavior in non-reversible stochastic processes. While our method is general, it is strongly motivated by discrete simulations of ordinary differential equations representing non-reversible biological processes, in particular molecular simulations. Here, the discrete time steps of the simulation are often very small compared to the time scale of interest, i.e., of the whole process. In this setting, the detection of a global cyclic behavior of the process becomes difficult because transitions between individual states may appear almost reversible on the small time scale of the simulation. We address this difficulty using a mixed-integer programming model that allows us to compute a cycle of clusters with maximum net flow, i.e., large forward and small backward probability. For a synthetic genetic regulatory network consisting of a ring-oscillator with three genes, we show that this approach can detect the most productive overall cycle, outperforming classical spectral analysis methods. Our method applies to general non-equilibrium steady state systems such as catalytic reactions, for which the objective value computes the effectiveness of the catalyst.
    Language: English
    Type: article , doc-type:article
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 10
    Publication Date: 2022-03-11
    Description: In this paper, we present a new, optimization-based method to exhibit cyclic behavior in non-reversible stochastic processes. While our method is general, it is strongly motivated by discrete simulations of ordinary differential equations representing non-reversible biological processes, in particular molecular simulations. Here, the discrete time steps of the simulation are often very small compared to the time scale of interest, i.e., of the whole process. In this setting, the detection of a global cyclic behavior of the process becomes difficult because transitions between individual states may appear almost reversible on the small time scale of the simulation. We address this difficulty using a mixed-integer programming model that allows us to compute a cycle of clusters with maximum net flow, i.e., large forward and small backward probability. For a synthetic genetic regulatory network consisting of a ring-oscillator with three genes, we show that this approach can detect the most productive overall cycle, outperforming classical spectral analysis methods. Our method applies to general non-equilibrium steady state systems such as catalytic reactions, for which the objective value computes the effectiveness of the catalyst.
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...