Approximability of scheduling with fixed jobs
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
The Multiple Subset Sum Problem
SIAM Journal on Optimization
A 3/4-Approximation Algorithm for Multiple Subset Sum
Journal of Heuristics
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
A Polynomial Time Approximation Scheme for the Multiple Knapsack Problem
SIAM Journal on Computing
Improved approximation algorithms for scheduling with fixed jobs
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
The effect of machine availability on the worst-case performance of LPT
Discrete Applied Mathematics
Approximation algorithms for scheduling with reservations
HiPC'07 Proceedings of the 14th international conference on High performance computing
Parameterized Approximation Scheme for the Multiple Knapsack Problem
SIAM Journal on Computing
Decision Support and Optimization in Shutdown and Turnaround Scheduling
INFORMS Journal on Computing
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We study the problem of scheduling jobs on identical parallel machines without preemption. In the considered setting, some of the jobs are already assigned machines and starting times, for example due to external constraints not explicitly modelled. The objective is to assign the rest of the jobs in order to minimize the makespan. It is known that this problem cannot be approximated better than within a factor of 3/2 unless P = NP. An algorithm that achieves 3/2 + ε for any ε 0 was presented by Diedrich and Jansen [DJ09], but its running time is doubly exponential in 1/ε. We present an improved algorithm with approximation ratio 3/2 and polynomial running time. We also give matching results for the related problem of scheduling with reservations. The new algorithm is both faster and conceptually simpler than the previously known algorithms.