M. R. Garey

The Complexity of Flowshop and Jobshop Scheduling

NP-complete problems form an extensive equivalence class of combinatorial problems for which no nonenumerative algorithms are known. Our first result shows that determining a shortest-length schedule in an m-machine flowshop is NP-complete for m ≥ 3. For m = 2, there is an efficient algorithm for finding such schedules. The second result shows that determining a minimum mean-flow-time schedule in an m-machine flowshop is NP-complete for every m ≥ 2. Finally we show that the shortest-length schedule problem for an m-machine jobshop is NP-complete for every m ≥ 2. Our 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 the task lengths.

Some simplified NP-complete graph problems

Abstract It is widely believed that showing a problem to be NP -complete is tantamount to proving its computational intractability. In this paper we show that a number of NP -complete problems remain NP -complete even when their domains are substantially restricted. First we show the completeness of Simple Max Cut (Max Cut with edge weights restricted to value 1), and, as a corollary, the completeness of the Optimal Linear Arrangement problem. We then show that even if the domains of the Node Cover and Directed Hamiltonian Path problems are restricted to planar graphs, the two problems remain NP -complete, and that these and other graph problems remain NP -complete even when their domains are restricted to graphs with low node degrees. For Graph 3-Colorability, Node Cover, and Undirected Hamiltonian Circuit, we determine essentially the lowest possible upper bounds on node degree for which the problems remain NP -complete.

The Rectilinear Steiner Tree Problem is

An optimum rectilinear Steiner tree for a set A of points in the plane is a tree which interconnects A using horizontal and vertical lines of shortest possible total length. Such trees correspond to single net wiring patterns on printed backplanes which minimize total wire length. We show that the problem of determining this minimum length, given A, is NP-complete. Thus the problem of finding optimum rectilinear Steiner trees is probably computationally hopeless, and the emphasis of the literature for this problem on heuristics and special case algorithms is well justified. A number of intermediary lemmas concerning the NP-completeness of certain graph-theoretic problems are proved and may be of independent interest.

NP

The following abstract problem models several practical problems in computer science and operations research: given a list L of real numbers between 0 and l, place the elements of L into a minimum number

-Complete

L^ *

Worst-Case Performance Bounds for Simple One-Dimensional Packing Algorithms

of “bins” so that no bin contains numbers whose sum exceeds l. Motivated by the likelihood that an excessive amount of computation will be required by any algorithm which actually determines an optimal placement, we examine the performance of a number of simple algorithms which obtain “good” placements. The first-fit algorithm places each number, in succession, into the first bin in which it fits. The best-fit algorithm places each number, in succession, into the most nearly full bin in which it fits. We show that neither the first-fit nor the best-fit algorithm will ever use more than

An Application of Bin-Packing to Multiprocessor Scheduling

\frac{17}{10}L^ * + 2

The Transitive Reduction of a Directed Graph

bins. Furthermore, we outline a proof that, if L is in decreasing order, then neither algorithm will use more than

The Complexity of Computing Steiner Minimal Trees

\frac{11}{9} L^ * + 4

Complexity Results for Multiprocessor Scheduling under Resource Constraints

bins. Examples are given to show that both upper bou...