NP-complete scheduling problems
TLDR
It is shown that the problem of finding an optimal schedule for a set of jobs is NP-complete even in the following two restricted cases, tantamount to showing that the scheduling problems mentioned are intractable.About:
This article is published in Journal of Computer and System Sciences.The article was published on 1975-06-01 and is currently open access. It has received 1356 citations till now. The article focuses on the topics: Multiprocessor scheduling & Fixed-priority pre-emptive scheduling.read more
Citations
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Book ChapterDOI
Optimization and Approximation in Deterministic Sequencing and Scheduling: a Survey
TL;DR: In this article, the authors survey the state of the art with respect to optimization and approximation algorithms and interpret these in terms of computational complexity theory, and indicate some problems for future research and include a selective bibliography.
Journal ArticleDOI
Variable neighborhood search
Nenad Mladenović,Pierre Hansen +1 more
TL;DR: This chapter presents the basic schemes of VNS and some of its extensions, and presents five families of applications in which VNS has proven to be very successful.
Journal ArticleDOI
Performance-effective and low-complexity task scheduling for heterogeneous computing
TL;DR: Two novel scheduling algorithms for a bounded number of heterogeneous processors with an objective to simultaneously meet high performance and fast scheduling time are presented, called the Heterogeneous Earliest-Finish-Time (HEFT) algorithm and the Critical-Path-on-a-Processor (CPOP) algorithm.
Journal ArticleDOI
The Complexity of Flowshop and Jobshop Scheduling
TL;DR: The results are strong in that they hold whether the problem size is measured by number of tasks, number of bits required to express the task lengths, or by the sum of thetask lengths.
References
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Book
The Design and Analysis of Computer Algorithms
Alfred V. Aho,John E. Hopcroft +1 more
TL;DR: This text introduces the basic data structures and programming techniques often used in efficient algorithms, and covers use of lists, push-down stacks, queues, trees, and graphs.
Reducibility Among Combinatorial Problems.
TL;DR: Throughout the 1960s I worked on combinatorial optimization problems including logic circuit design with Paul Roth and assembly line balancing and the traveling salesman problem with Mike Held, which made me aware of the importance of distinction between polynomial-time and superpolynomial-time solvability.
Proceedings ArticleDOI
The complexity of theorem-proving procedures
TL;DR: It is shown that any recognition problem solved by a polynomial time-bounded nondeterministic Turing machine can be “reduced” to the problem of determining whether a given propositional formula is a tautology.
Journal ArticleDOI
Optimal scheduling for two-processor systems
Edward G. Coffman,Ron Graham +1 more
TL;DR: It is proved that the algorithm gives optimal solutions and its application to preemptive scheduling disciplines is discussed.
Journal ArticleDOI
Scheduling independent tasks to reduce mean finishing time
TL;DR: It is shown that the most general mean-finishing-time problem for independent tasks is polynomial complete, and hence unlikely to admit of a non-enumerative solution.