Approximation algorithms for scheduling unrelated parallel machines
- J. Lenstra, D. Shmoys, É. Tardos
- Business28th Annual Symposium on Foundations of Computer…
- 12 October 1987
It is proved that no polynomial algorithm can achieve a worst-case ratio less than 3/2 unless P = NP, and a complexity classification for all special cases with a fixed number of processing times is obtained.
An approximation algorithm for the generalized assignment problem
The generalized assignment problem can be viewed as the following problem of scheduling parallel machines with costs. Each job is to be processed by exactly one machine; processing jobj on machinei…
The Design of Approximation Algorithms
- David P. Williamson, D. Shmoys
- Computer Science
- 26 April 2011
This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions to discrete optimization problems.
Fast approximation algorithms for fractional packing and covering problems
- Serge A. Plotkin, D. Shmoys, É. Tardos
- Computer Science[] Proceedings 32nd Annual Symposium of…
- 1 September 1991
Fast algorithms that find approximate solutions for a general class of problems, which are called fractional packing and covering problems, are presented, and an important result is a theoretical analysis of the running time of a Lagrangian relaxation based algorithm.
Sequencing and scheduling: algorithms and complexity
- E. Lawler, J. Lenstra, Ahg Alexander Rinnooy Kan, D. Shmoys
- Business
- 1989
This survey focuses on the area of deterministic machine scheduling, and reviews complexity results and optimization and approximation algorithms for problems involving a single machine, parallel machines, open shops, flow shops and job shops.
Using dual approximation algorithms for scheduling problems: Theoretical and practical results
- D. Hochbaum, D. Shmoys
- Computer Science26th Annual Symposium on Foundations of Computer…
- 21 October 1985
A new approach to constructing approximation algorithms, which the aim is find superoptimal, but infeasible solutions, and the performance is measured by the degree of infeasibility allowed, which should find wide applicability for any optimization problem where traditional approximation algorithms have been particularly elusive.
A Best Possible Heuristic for the k-Center Problem
- D. Hochbaum, D. Shmoys
- Computer Science, MathematicsMathematics of Operations Research
- 1 May 1985
A 2-approximation algorithm for the k-center problem with triangle inequality is presented, the key combinatorial object used is called a strong stable set, and the NP-completeness of the corresponding decision problem is proved.
Approximation algorithms for facility location problems
- D. Shmoys
- Computer ScienceInternational Workshop on Approximation…
- 5 September 2000
This note is intended as companion to the lecture at CONF 2000, mainly to give pointers to the appropriate references.
Dynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint
- Paat Rusmevichientong, Z. Shen, D. Shmoys
- Computer ScienceOperational Research
- 1 November 2010
This work develops an adaptive policy that learns the unknown parameters from past data and at the same time optimizes the profit and develops a simple algorithm for computing a profit-maximizing assortment based on the geometry of lines in the plane.
Improved Approximation Algorithms for the Uncapacitated Facility Location Problem
- Fabián A. Chudak, D. Shmoys
- Computer ScienceSIAM journal on computing (Print)
- 2003
A (1+2/e)-approximation algorithm is obtained, which is a significant improvement on the previously known approximation guarantees, and works by rounding an optimal fractional solution to a linear programming relaxation.
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