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ORCIDComputational Optimization and Applications, Volume 3
Volume 3, Number 1, March 1994
- Jeffery L. Kennington, Farin Mohammadi:
The singly constrained assignment problem: A Lagrangian relaxation heuristic algorithm. 7-26 - Aubrey B. Poore:
Multidimensional assignment formulation of data association problems arising from multitarget and multisensor tracking. 27-57 - Diana S. Yakowitz:
A regularized stochastic decomposition algorithm for two-stage stochastic linear programs. 59-81 - Zhi-Quan Luo, Shi-Quan Wu:
A modified predictor-corrector method for linear programming. 83-91
Volume 3, Number 2, May 1994
- Djangir A. Babayev, Sahib S. Mardanov:
Reducing the number of variables in Integer and Linear Programming Problems. 99-109 - Pamela H. Vance, Cynthia Barnhart
, Ellis L. Johnson, George L. Nemhauser:
Solving binary cutting stock problems by column generation and branch-and-bound. 111-130 - Renato D. C. Monteiro, Stephen J. Wright:
Local convergence of interior-point algorithms for degenerate monotone LCP. 131-155 - Xiaojun Chen, Liqun Qi:
A parameterized Newton method and a quasi-Newton method for nonsmooth equations. 157-179 - Hiroshi Konno, Yasutoshi Yajima, Ayumi Ban:
Calculating a minimal sphere containing a polytope defined by a system of linear inequalities. 181-191
Volume 3, Number 3, July 1994
- Stavros A. Zenios:
Data parallel computing for network-structured optimization problems. 199-242 - Carlo Mannino, Antonio Sassano:
An exact algorithm for the maximum stable set problem. 243-258 - Ahmed Roubi:
Global convergence and rate of convergence of a method of centers. 259-280
Volume 3, Number 4, October 1994
- Neculai Andrei:
Introduction. 287-288 - Yuri G. Evtushenko, Vitali G. Zhadan:
Stable barrier-projection and barrier-Newton methods in linear programming. 289-303 - Michael J. Todd:
Scaling, shifting and weighting in interior-point methods. 305-315 - Uwe H. Suhl, Ralf Szymanski:
Supernode processing of mixed-integer models. 317-331 - Ralph E. Steuer:
Random problem generation and the computation of efficient extreme points in multiple objective linear programming. 333-347 - James K. Ho, R. P. Sundarraj:
On the efficacy of distributed simplex algorithms for linear programming. 349-363
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