Minimizing mean flow time in two-machine open shops and flow shops
Journal of Algorithms
Computing Partitions with Applications to the Knapsack Problem
Journal of the ACM (JACM)
Journal of Computer and System Sciences - Special issue on the fourteenth annual IEE conference on computational complexity
Which problems have strongly exponential complexity?
Journal of Computer and System Sciences
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Non-Approximability Results for Scheduling Problems with Minsum Criteria
INFORMS Journal on Computing
Complexity Theory: Exploring the Limits of Efficient Algorithms
Complexity Theory: Exploring the Limits of Efficient Algorithms
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
Graph balancing: a special case of scheduling unrelated parallel machines
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
There is no EPTAS for two-dimensional knapsack
Information Processing Letters
On the possibility of faster SAT algorithms
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Exact Exponential Algorithms
A fast approximation scheme for the multiple knapsack problem
SOFSEM'12 Proceedings of the 38th international conference on Current Trends in Theory and Practice of Computer Science
Bin packing with fixed number of bins revisited
Journal of Computer and System Sciences
Parameterized Complexity and Approximation Algorithms
The Computer Journal
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We investigate the implications of the exponential time hypothesis on algorithms for scheduling and packing problems. Our main focus is to show tight lower bounds on the running time of these algorithms. For exact algorithms we investigate the dependence of the running time on the number n of items (for packing) or jobs (for scheduling). We show that many of these problems, including SubsetSum, Knapsack, BinPacking, 〈P2 | | C max 〉, and 〈P2 | |∑wjCj〉, have a lower bound of 2o(n) ×∥I∥O(1). We also develop an algorithmic framework that is able to solve a large number of scheduling and packing problems in time 2O(n) ×∥I∥O(1). Finally, we show that there is no PTAS for MultipleKnapsack and 2d-Knapsack with running time $2^{o}({\frac{1}{\epsilon }}) \times \parallel I \parallel^{O(1)}$ and $n^{o({\frac{1}{\epsilon }})} \times \parallel{I}\parallel^{O(1)}$.