COIN-OR::LEMON - Graph Library

Changes between Version 8 and Version 9 of AlkMod2017


Ignore:
Timestamp:
10/26/17 09:52:40 (2 years ago)
Author:
Alpar Juttner
Comment:

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  • AlkMod2017

    v8 v9  
    22
    33== November 8. ==
     4
     5Heurisztikák és egzakt módszerek az Utazó ügynök problémára.
     6
     7== November 15. ==
     8
    49[attachment:SolvingHuge.pdf​ C. Barnhart, E. L. Johnson, G. L. Nemhauser, M. W.P. Savelsbergh, P. H. Vance. ''Branch-and-Price: Column Generation for Solving Huge Integer Programs'']
    510
    611We discuss formulations of integer programs with a huge number of variables and their solution by column generation methods, i.e. implicit pricing of nonbasic variables to generate new columns or to prove LP optimality at a node of the branch-and-bound tree. We present classes of models for which this approach decomposes the problem, provides tighter LP relaxations and eliminates symmetry. We then discuss computational issues and implementation of column generation, branch-and-bound algorithms, including special branching rules and effient ways to solve the LP relaxation.
    712
    8 == November 15. ==
     13== November 22. ==
    914
    1015[attachment:a02v29n2.pdf​ D. P. Ronconi and M. S. Kawamura. ''The single machine earliness and tardiness scheduling problem: lower bounds and a branch-and-bound algorithm'']
     
    1217This paper addresses the single machine scheduling problem with a common due date aiming to minimize earliness and tardiness penalties. Due to its complexity, most of the previous studies in the literature deal with this problem using heuristics and metaheuristics approaches. With the intention of contributing to the study of this problem, a branch-and-bound algorithm is proposed. Lower bounds and pruning rules that exploit properties of the problem are introduced. The proposed approach is examined through a computational comparative study with 280 problems involving different due date scenarios. In addition, the values of optimal solutions for small problems from a known benchmark are provided.
    1318
    14 == November 22. ==
    15 
     19== November 29. ==
    1620
    1721[attachment:garg97faster.pdf​ Naveen Garg, Jochen Konemann. ''Faster and Simpler Algorithms for Multicommodity Flow and other Fractional Packing Problems'']
     
    1923This paper considers the problem of designing fast, approximate, combinatorial algorithms for multicommodity flows and other fractional packing problems. We provide a different approach to these problems which yields faster and much simpler algorithms. Our approach also allows us to substitute shortest path computations for min-cost flow computations in computing maximum concurrent flow and min-cost multicommodity flow; this yields much faster algorithms when the number of commodities is large.
    2024
    21 == November 29. ==
     25== December 6. ==
    2226
    2327[attachment:LecturesIntroBundle.pdf​ Alexandre Belloni. ''Lecture Notes for IAP 2005 Course Introduction to Bundle Methods'']
    2428
    25 == December 6. ==
     29== December 13. ==
    2630
    2731[attachment:515123.pdf​ Marjan van den Akker, Han Hoogeveen, Steef van de Velde. ''COMBINING COLUMN GENERATION AND LAGRANGEAN RELAXATION ---
     
    3337Our vehicle to demonstrate the effectiveness of teaming up column generation with Lagrangean relaxation is an archetypical single-machine common due date scheduling problem. Our comprehensive computational study shows that the combined algorithm is by far superior to two existing purely column generation algorithms: it solves instances with up to 125 jobs to optimality, while purely column generation algorithm can solve instances with up to only 60 jobs.
    3438
    35 == December 13. ==
     39== Ez is választható ==
    3640
    3741[attachment:EURO2001.pdf​ Edson L. F. Senne, Luiz A. N. Lorena. ''Stabilizing column generation using Lagrangean/surrogate relaxation: an application to p-median location problems'']