Preprocessing under uncertainty

In this work we study preprocessing for tractable problems when part of the input is unknown or uncertain. This comes up naturally if, e.g., the load of some machines or the congestion of some roads is not known far enough in advance, or if we have to regularly solve a problem over instances that are largely similar, e.g., daily airport scheduling with few charter flights. Unlike robust optimization, which also studies settings like this, our goal lies not in computing solutions that are (approximately) good for every instantiation. Rather, we seek to preprocess the known parts of the input, to speed up finding an optimal solution once the missing data is known. We present efficient algorithms that given an instance with partially uncertain input generate an instance of size polynomial in the amount of uncertain data that is equivalent for every instantiation of the unknown part. Concretely, we obtain such algorithms for Minimum Spanning Tree, Minimum Weight Matroid Basis, and Maximum Cardinality Bipartite Maxing, where respectively the weight of edges, weight of elements, and the availability of vertices is unknown for part of the input. Furthermore, we show that there are tractable problems, such as Small Connected Vertex Cover, for which one cannot hope to obtain similar results.Comment: 18 page

Equidistribution in All Dimensions of Worst-Case Point Sets for the TSP

Given a set S of n points in the unit square [0, 1]d , an optimal traveling salesman tour of S is a tour of S that is of minimum length. A worst-case point set for the Traveling Salesman Problem in the unit square is a point set S(n) whose optimal traveling salesman tour achieves the maximum possible length among all point sets S ⊂ [0, 1]d , where |S| = n. An open problem is to determine the structure of S(n) . We show that for any rectangular parallelepiped R contained in [0, 1]d , the number of points in S(n) ∩ R is asymptotic to n times the volume of R. Analogous results are proved for the minimum spanning tree, minimum-weight matching, and rectilinear Steiner minimum tree. These equidistribution theorems are the first results concerning the structure of worst-case point sets like S(n)

Equidistribution of Point Sets for the Traveling Salesman and Related Problems

Given a set S of n points in the unit square [0, 1)2, an optimal traveling salesman tour of S is a tour of S that is of minimum length. A worst-case point set for the Traveling Salesman Problem in the unit square is a point set S(n) whose optimal traveling salesman tour achieves the maximum possible length among all point sets S C [0, 1)2, where JSI = n. An open problem is to determine the structure of S(n). We show that for any rectangle R contained in [0, 1 F, the number of points in S(n) n R is asymptotic to n times the area of R. One corollary of this result is an 0( n log n) approximation algorithm for the worst-case Euclidean TSP. Analogous results are proved for the minimum spanning tree, minimum-weight matching, and rectilinear Steiner minimum tree. These equidistribution theorems are the first results concerning the structure of worst-case point sets like S(n)

Streaming and Dynamic Algorithms for Minimum Enclosing Balls in High Dimensions

At SODA'10, Agarwal and Sharathkumar presented a streaming algorithm for approximating the minimum enclosing ball of a set of points in d-dimensional Euclidean space. Their algorithm requires one pass, uses O(d) space, and was shown to have approximation factor at most 1.3661. We prove that the same algorithm has approximation factor less than 1.22, which brings us much closer to a 1.207 lower bound given by Agarwal and Sharathkumar. We also apply this technique to the dynamic version of the minimum enclosing ball problem (in the non-streaming setting). We give an O(dn)-space data structure that can maintain a 1.22-approximate minimum enclosing ball in O(dlog n) expected amortized time per insertion/deletion. Finally, we prove that a 1+ϵ approximation to the problem can be found in (0.5+δ)/ϵ passes over the input, for an arbitrarily small constant δ, which is an improvement over the previous result that used 2/ϵ passes

Development and Evaluation of Interactive Courseware for Visualization of Graph Data Structure and Algorithms

The primary goal of this dissertation was to develop and pilot test interactive, multimedia courseware which would facilitate learning the abstract structures, operations, and concepts associated with graph and network data structures in Computer Science. Learning objectives and prerequisites are presented in an introduction section of the courseware and a variety of learning activities are provided including tutorials, animated demonstrations, interactive laboratory sessions, and self-tests. Courseware development incorporated principles and practices from software engineering, instructional design, and cognitive learning theories. Implementation utilized an easy-to-use authoring tool, NeoBook Professional (1994), to create the overall framework and the user interfaces, and Microsoft QuickBASIC 4.5 (1990) to program the interactive animated demonstrations and laboratory exercises. A major emphasis of the courseware is the use of simple interactive, animated displays to demonstrate the step-by-step operation of graph and network algorithms such as depth-first traversal, breadth-first traversal, shortest path, minimum sparring tree and topological ordering

Logistics service network design : models, algorithms, and applications

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2004.Includes bibliographical references (leaves 177-186).Service network design is critical to the profitability of express shipment carriers. In this thesis, we consider two challenging problems associated with designing networks for express shipment service. The first problem is to design an integrated network for premium and deferred services simultaneously. Related existing models adapted to this problem are intractable for realistic instances of this problem: computer memory requirements and solution times are excessive. We introduce a disaggregate information-enhanced column generation approach for this problem that reduces the number of variables to be considered in the integer program from hundreds of thousands to only thousands, allowing us to solve previously unsolvable problem instances. The second problem is to determine the express package service network design in its entirety, including aircraft routings, fleet assignments, and package flow routings, including hub assignments. Existing models applied to this problem have weak associated linear programming bounds and hence, fail to produce quality feasible solutions. For example, for a small network design problem instance it takes days to produce a feasible solution that is provably near- optimal using the best performing existing model. To overcome these tractability challenges, we introduce a new model, referred to as the gateway cover and flow formulation. Applying our new formulation to the same network design instance, it takes only minutes to find an optimal solution.(cont.) Applying our disaggregate information-enhanced column generation approach and gateway cover and flow formulation and solution approach to the network design problems of a large express package service provider, we demonstrate tens of millions of dollars in potential annual operating cost savings and reductions in the numbers of aircraft needed to perform the service. Moreover, we illustrate that, though designed for tactical planning, our new model and solution approach can provide insights for strategic decision-making, such as hub opening/closure, hub capacity expansion, and fleet composition and size.by Su Shen.Ph.D

EQUIDISTRIBUTION IN ALL DIMENSIONS OF WORST-CASE POINT SETS FOR THE TRAVELING SALESMAN PROBLEM

Given a set S of n points in the unit square [0,1] d, an optimal traveling salesman tour of S is a tour of S that is of minimum length. A worst-case point set for the traveling salesman problem in the unit square is a point set S (n) whose optimal traveling salesman tour achieves the maximum possible length among all point sets S C [0, 1] d, where IS n. An open problem is to determine the structure of S(n). We show that for any rectangular parallelepiped R contained in [0, 1] d, the number of points in S (n) N R is asymptotic to n times the volume of R. Analogous results are proved for the minimum spanning tree, minimum-weight matching, and rectilinear Steiner minimum tree. These equidistribution theorems are the first results concerning the structure of worst-case point sets like S(n)

A General Approximation Technique For Constrained Forest Problems

We present a general approximation technique for a large class of graph problems. Our technique mostly applies to problems of covering, at minimum cost, the vertices of a graph with trees, cycles or paths satisfying certain requirements. In particular, many basic combinatorial optimization problems fit in this framework, including the shortest path, minimum-cost spanning tree, minimum-weight perfect matching, traveling salesman and Steiner tree problems. Our techniqueproduces approximation algorithms that run in O(n² log n) time and come within a factor of 2 of optimal for most of these problems. For instance, we obtain a 2-approximationalgorithm for the minimum-weight perfect matching problem under the triangle inequality. Our running time of O(n² log n) time compares favorably with the best strongly polynomial exact algorithms running in O(n³) time for dense graphs. A similar result is obtained for the 2-matchingproblem and its variants. We also derive the first approxi..