A survey of results for sequencing problems with controllable processing times
Discrete Applied Mathematics - Southampton conference on combinatorial optimization, April 1987
An approximation algorithm for the generalized assignment problem
Mathematical Programming: Series A and B
Discrete Applied Mathematics
Approximability and nonapproximability results for minimizing total flow time on a single machine
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Approximation algorithms for NP-hard problems
Approximation algorithms for NP-hard problems
Approximating total flow time on parallel machines
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Minimizing the flow time without migration
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Flow and stretch metrics for scheduling continuous job streams
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
On Preemptive Scheduling of Unrelated Parallel Processors by Linear Programming
Journal of the ACM (JACM)
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A PTAS for the Single Machine Scheduling Problem with Controllable Processing Times
SWAT '02 Proceedings of the 8th Scandinavian Workshop on Algorithm Theory
Job Shop Scheduling Problems with Controllable Processing Times
ICTCS '01 Proceedings of the 7th Italian Conference on Theoretical Computer Science
Single machine scheduling with discretely controllable processing times
Operations Research Letters
A survey of scheduling with controllable processing times
Discrete Applied Mathematics
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In a scheduling problem with controllable processing times the job processing time can be compressed through incurring an additional cost. We consider the identical parallel machines max flow time minimization problem with controllable processing times. We address the preemptive and non-preemptive version of the problem. For the preemptive case, a linear programming formulation is presented which solves the problem optimally in polynomial time. For the non-preemptive problem it is shown that the First In First Out (FIFO) heuristic has a tight worst-case performance of 3 - 2/m, when jobs processing times and costs are set as in some optimal preemptive schedule.