Genetic Algorithm for the Jump Number Scheduling Problem

This paper introduces genetic algorithms for the jump number scheduling problem. Given a set of tasks subject to precedence constraints, the problem is to construct a schedule to minimize the number of jumps. We show that genetic algorithms outperform the previously known Knuth and Szwarcfiter's exhaustive search algorithm when applied to some classes of orders in which no polynomial time algorithms exist in solving the jump number problem. Values for various parameters of genetic jump number algorithms are tested and results are discussed.     

Tackling the jump number of interval orders

Although the jump number problem for partially ordered sets in NP-complete in general, there are some special classes of posets for which polynomial time algorithms are known.Here we prove that for the class of interval orders the problem remains NP-complete. Moreover we describe another 3/2-approximation algrithm (two others have been developed already by Felsner and Syslo, respectively) by using a polynomial time subgraph packing algorithm.     

Bicliques in Graphs I: Bounds on Their Number

Bicliques are inclusion-maximal induced complete bipartite subgraphs in graphs. Upper bounds on the number of bicliques in bipartite graphs and general graphs are given. Then those classes of graphs where the number of bicliques is polynomial in the vertex number are characterized, provided the class is closed under induced subgraphs. Received January 27, 1997     

N-fold integer programming and nonlinear multi-transshipment

The multi-transshipment problem is NP-hard already for two commodities over bipartite networks. Nonetheless, using our recent theory of n-fold integer programming and extensions developed herein, we are able to establish the polynomial time solvability of the problem in two broad situations. First, for any fixed number of commodities and number of suppliers, we solve the problem over bipartite networks with variable number of consumers in polynomial time. This is very natural in operations research applications where few facilities serve many customers. Second, for every fixed network, we solve the problem with variable number of commodities in polynomial time.     

Related necessary conditions for completing partial latin squares

Three classes of necessary conditions for completing partial latin squares are studied. These condition classes are derived via network flow theory, bipartite graph matching theory and by relating the completion problem to triply stochastic matrices. The latter formulation suggest an integer programming model of the completion problem which is convenient for analyzing the relative strength of the three condition classes. It is shown that these classes are nested and examples are given to demonstrate that this nesting is proper.     

Minimizing setups in ordered sets of fixed width

A simply polynomial time algorithm is given for computing the setup number, or jump number, of an ordered set with fixed width. This arises as an interesting application of a polynomial time algorithm for solving a more general weighted problem in precedence constrained scheduling.     

The Exact Weighted Independent Set Problem in Perfect Graphs and Related Classes

The exact weighted independent set (EWIS) problem consists in determining whether a given vertex-weighted graph contains an independent set of given weight. This problem is a generalization of two well-known problems, the NP-complete subset sum problem and the strongly NP-hard maximum weight independent set (MWIS) problem. Since the MWIS problem is polynomially solvable for some special graph classes, it is interesting to determine the complexity of this more general EWIS problem for such graph classes.We focus on the class of perfect graphs, which is one of the most general graph classes where the MWIS problem can be solved in polynomial time. It turns out that for certain subclasses of perfect graphs, the EWIS problem is solvable in pseudo-polynomial time, while on some others it remains strongly NP-complete. In particular, we show that the EWIS problem is strongly NP-complete for bipartite graphs of maximum degree three, but solvable in pseudo-polynomial time for cographs, interval graphs and chordal graphs, as well as for some other related graph classes.     

Clustering and domination in perfect graphs

A k-cluster in a graph is an induced subgraph on k vertices which maximizes the number of edges. Both the k-cluster problem and the k-dominating set problem are NP-complete for graphs in general. In this paper we investigate the complexity status of these problems on various sub-classes of perfect graphs. In particular, we examine comparability graphs, chordal graphs, bipartite graphs, split graphs, cographs and κ-trees. For example, it is shown that the k-cluster problem is NP-complete for both bipartite and chordal graphs and the independent k-dominating set problem is NP-complete for bipartite graphs. Furthermore, where the k-cluster problem is polynomial we study the weighted and connected versions as well. Similarly we also look at the minimum k-dominating set problem on families which have polynomial k-dominating set algorithms.     

Complexity and approximation results for the connected vertex cover problem in graphs and hypergraphs

We study a variation of the vertex cover problem where it is required that the graph induced by the vertex cover is connected. We prove that this problem is polynomial in chordal graphs, has a PTAS in planar graphs, is APX-hard in bipartite graphs and is 5/3-approximable in any class of graphs where the vertex cover problem is polynomial (in particular in bipartite graphs). Finally, dealing with hypergraphs, we study the complexity and the approximability of two natural generalizations.     

On finding the jump number of a partial orber by substitution decomposition

Consider the linear extensions of a partial order. A jump occurs in a linear extension if two consecutive elements are unrelated in the partial order. The jump number problem is to find a linear extension of the ordered set which contains the smallest possible number of jumps. We discuss a decomposition approach for this problem from an algorithmic point of view. Based on this some new classes of partial orders are identified, for which the problem is polynomially solvable.     

带工件相容约束的单机分批排序问题

The single machine parallel batch problem with job compatibility is considered to minimize makespan,where the job compatibility constraints are represented by a graph G.This problem is proved to be NP-hard.And when the graph G is limited to be a general bipartite,a complete bipartite and a complete m-partite graph,these problems are solved in polynomial time respectively.     

Weakly bipartite graphs and the Max-cut problem

A new class of graphs, called weakly bipartite graphs, is introduced. A graph is called weakly bipartite if its bipartite subgraph polytope coincides with a certain polyhedron related to odd cycle constraints. The class of weakly bipartite graphs contains for instance the class of bipartite graphs and the class of planar graphs. It is shown that the max-cut problem can be solved in polynomial time for weakly bipartite graphs. The polynomical algorithm presented is based on the ellipsoid method and an algorithm that computes a shortest path of even length.     

Scheduling unit-length jobs with precedence constraints of small height

We consider the problem of scheduling unit-length jobs on identical machines subject to precedence constraints. We show that natural scheduling rules fail when the precedence constraints form a collection of stars or a collection of complete bipartite graphs. We prove that the problem is in fact NP-hard on collections of stars when the input is given in a compact encoding, whereas it can be solved in polynomial time with standard adjacency list encoding. On a subclass of collections of stars and on collections of complete bipartite graphs we show that the problem can be solved in polynomial time even when the input is given in compact encoding, in both cases via non-trivial algorithms.     

Stochastic Enumeration Method for Counting Trees

The problem of estimating the size of a backtrack tree is an important but hard problem in the computational sciences. An efficient solution of this problem can have a major impact on the hierarchy of complexity classes. The first randomized procedure, which repeatedly generates random paths through the tree, was introduced by Knuth. Unfortunately, as was noted by Knuth and a few other researchers, the estimator can introduce a large variance and become ineffective in the sense that it underestimates the cost of the tree. Recently, a new sequential algorithm called Stochastic Enumeration (SE) method was proposed by Rubinstein et al. The authors showed numerically that this simple algorithm can be very efficient for handling different counting problems, such as counting the number of satisfiability assignments and enumerating the number of perfect matchings in bipartite graphs. In this paper we introduce a rigorous analysis of SE and show that it results in significant variance reduction as compared to Knuth’s estimator. Moreover, we establish that for almost all random trees the SE algorithm is a fully polynomial time randomized approximation scheme (FPRAS) for the estimation of the overall tree size.     

On the inverse problem of linear programming and its application to minimum weight perfect k-matching

We first introduce the inverse problem of linear programming. We then apply it to the inverse problem of minimum weight perfect k-matching of bipartite graphs. We show that there is a strongly polynomial algorithm for solving the problem.     

两类广义控制问题的NP-完全性

研究两类广义控制问题的复杂性: k-步长控制问题和k-距离控制问题, 证明了k-步长控制问题在弦图和平面二部图上都是NP-完全的. 作为上述结果的推论, 给出了k-距离控制问题在弦图和二部图上NP-完全性的新的证明, 并进一步证明了k-距离控制问题在平面二部图上也是NP-完全的.     

Enumerative Properties of Ferrers Graphs

We define a class of bipartite graphs that correspond naturally with Ferrers diagrams. We give expressions for the number of spanning trees, the number of Hamiltonian paths when applicable, the chromatic polynomial and the chromatic symmetric function. We show that the linear coefficient of the chromatic polynomial is given by the excedance set statistic.     

The bipartite margin shop and maximum red matchings free of blue–red alternating cycles

The margin shop arises as a model of margining investment portfolios in a batch, a mandatory end-of-day risk management operation for any prime brokerage firm. The margin-shop scheduling problem is the extension of the preemptive flow-shop scheduling problem where precedence constraints can be introduced between preempted parts of jobs. This paper is devoted to the bipartite case which is equivalent to the problem of finding a maximum red matching that is free of blue–red alternating cycles in a complete bipartite graph with blue and red edges. It is also equivalent to the version of the jump-number problem for bipartite posets where jumps inside only one part should be counted. We show that the unit-time bipartite margin-shop scheduling problem is NP-hard but can be solved in polynomial time if the precedence graph is of degree at most two or a forest.     

Parameterized complexity of the weighted independent set problem beyond graphs of bounded clique number

The maximum independent set problem is known to be NP-hard for graphs in general, but is solvable in polynomial time for graphs in many special classes. It is also known that the problem is generally intractable from a parameterized point of view. A simple Ramsey argument implies the fixed-parameter tractability of the maximum independent set problem in classes of graphs of bounded clique number. Beyond this observation very little is known about the parameterized complexity of the problem in restricted graph families. In the present paper we develop fpt-algorithms for graphs in some classes extending graphs of bounded clique number.     

A 3/2-approximation algorithm for the jump number of interval orders

The jump number of a partial order P is the minimum number of incomparable adjacent pairs in some linear extension of P. The jump number problem is known to be NP-hard in general. However some particular classes of posets admit easy calculation of the jump number.The complexity status for interval orders still remains unknown. Here we present a heuristic that, given an interval order P, generates a linear extension , whose jump number is less than 3/2 times the jump number of P.This work was supported by the Deutsche Forschungsgemeinschaft (DFG).