A unified approach to scheduling on unrelated parallel machines

Author:

Kumar V. S. Anil1,Marathe Madhav V.1,Parthasarathy Srinivasan2,Srinivasan Aravind3

Affiliation:

1. Virginia Tech., Blacksburg, Virginia

2. IBM T. J. Watson Research Center, Hawthorne, New York

3. University of Maryland, College Park, Maryland

Abstract

We develop a single rounding algorithm for scheduling on unrelated parallel machines; this algorithm works well with the known linear programming-, quadratic programming-, and convex programming-relaxations for scheduling to minimize completion time, makespan, and other well-studied objective functions. This algorithm leads to the following applications for the general setting of unrelated parallel machines: (i) a bicriteria algorithm for a schedule whose weighted completion-time and makespan simultaneously exhibit the current-best individual approximations for these criteria; (ii) better-than-two approximation guarantees for scheduling to minimize the L p norm of the vector of machine-loads, for all 1 < p < ∞; and (iii) the first constant-factor multicriteria approximation algorithms that can handle the weighted completion-time and any given collection of integer L p norms. Our algorithm has a natural interpretation as a melding of linear-algebraic and probabilistic approaches. Via this view, it yields a common generalization of rounding theorems due to Karp et al. [1987] and Shmoys & Tardos [1993], and leads to improved approximation algorithms for the problem of scheduling with resource-dependent processing times introduced by Grigoriev et al. [2007].

Funder

Centers for Disease Control and Prevention

National Science Foundation

National Institute of General Medical Sciences

Defense Threat Reduction Agency

Division of Computer and Network Systems

Division of Social and Economic Sciences

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Hardware and Architecture,Information Systems,Control and Systems Engineering,Software

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