30893368
Nonlinear Pattern Matching in Trees
Tree pattern matching is a fundamental operation that is used in a number of programming tasks such as mechanical theorem proving, term rewriting, symbolic computation and nonprocedural programming languages. In this paper we present new sequential algorithms for nonlinear pattern matching in trees. Our algorithm improves upon known tree pattern matching algorithms in important aspects such as time performance, ease of integration with several reduction strategies and ability to avoid unnecessary computation steps on match attempts that fail. The expected time complexity of our algorithm is linear in the sum of the sizes of the two trees.
42187803
Incremental Techniques for Efficient Normalization of Nonlinear Rewrite Systems
In [8] we described a nonlinear pattern-matching algorithm with the best known worst-case and optimal average-case time complexity. In this paper we first report on some experiments conducted on our algorithm. Based on these experiments we believe that our algorithm is useful in speeding up normalization of nonlinear rewrite systems even when it has a small number (≥5) of rewrite rules.
5663050
Term Matching on Parallel Computers
Term matching is an important problem that arises very often in term rewriting and in functional and equational programming. We present a new parallel algorithm for the term-matching problem on the EREW (exclusive read, exclusive write) model of parallel computation. Our algorithm assumes a string representation of the two terms as its input. The string representation is first transformed into two labeled ordered trees, and term matching is then performed on these two trees. If n is the length of the input terms, then for any constant ϵ (0 < ϵ ≤ 1) our algorithm uses O(n1-ϵ) processors and takes O(nϵlogn) time. If ϵ = 0, the same algorithm will run in O(log2 n) time. The only other known parallel algorithm for this problem, due to Dwork, Kanellakis, and Stockmeyer, requires O(n2) processors and takes either O(logn) or O(log2n) time. However, their algorithm uses the stronger CREW (concurrent read, exclusive write) model of parallel computation and assumes a DAG (directed acyclic graph) representation of the two terms as its input. On the CRCW (concurrent read, concurrent write) model our algorithm requires n processors and O(log n) time.
16348991
Adaptive Pattern Matching
Pattern matching is an important operation used in many applications such as functional programming, rewriting, and rule-based expert systems. By preprocessing the patterns into a DFA-like automaton, we can rapidly select the matching pattern(s) in a single scan of the relevant portions of the input term. This automaton is typically based on left-to-right traversal of the patterns. By adapting the traversal order to suit the set of input patterns, it is possible to considerably reduce the space and matching time requirements of the automaton. The design of such adaptive automata is the focus of this paper. We first formalize the notion of an adaptive traversal. We then present several strategies for synthesizing adaptive traversal orders aimed at reducing space and matching time complexity. In the worst case, however, the space requirements can be exponential in the size of the patterns. We show this by establishing an exponential lower bounds on space that is independent of the traversal order used. We then discuss an orthogonal approach to space minimization based on direct construction of optimal dag automata. Finally, our work brings forth the impact of typing in pattern matching. In particular, we show that several important problems (e.g., lazy pattern matching in ML) are computationally hard in the presence of type disciplines, whereas they can be solved efficiently in the untyped setting.
10316561
Variable-depth trie index optimization: theory and experimental results
We develop an efficient approach to Trie index optimization. A Trie is a data structure used to index a file having a set of attributes as record identifiers. In the proposed methodology, a file is horizontally partitioned into subsets of records using a Trie index whose depth of indexing is allowed to vary. The retrieval of a record from the file proceeds by “stepping through” the index to identify a subset of records in the file in which a binary search is performed. This paper develops a taxonomy of optimization problems underlying variable-depth Trie index construction. All these problems are solvable in polynomial time, and their characteristics are studied. Exact algorithms and heuristics for their solution are presented. The algorithms are employed in CRES-an expert system for editing written narrative material, developed for the Department of the Navy. CRES uses several large-to-very-large dictionary files for which Trie indexes are constructed using these algorithms. Computational experience with CRES shows that search and retrieval using variable-depth Trie indexes can be as much as six times faster than pure binary search. The space requirements of the Tries are reasonable. The results show that the variable-depth Tries constructed according to the proposed algorithms are viable and efficient for indexing large-to-very-large files by attributes in practical applications.
42876448
Optimal Speedups for Parallel Pattern Matching in Trees
Tree pattern matching is a fundamental operation that is used in a number of programming tasks such as code optimization in compilers, symbolic computation, automatic theorem proving and term rewriting. An important special case of this operation is linear tree pattern matching in which an instance of any variable in the pattern occurs at most once. If n and m are the number of nodes in the subject and pattern tree respectively and if no restriction is placed on the structure of the trees, then the fastest known sequential algorithm for linear tree pattern matching requires O(nm) time in the worst case.
60708157
Multicriteria jobshop scheduling
Abstract Jobshop scheduling is one of the important classes of problems in production planning. The jobshop represents a common manufacturing environmental, in which a set of machines is used to process a stream of jobs arriving randomly. The stochastic arrival pattern of the jobs, their processing sequences, and processing times render the scheduling of jobs in a jobshop a complex and difficult task. Furthermore, the scheduling task involves multiple conflicting objectives such as the minimization of the flow time, lateness and the number of late jobs among others. In this research, we develop a framework for the efficient scheduling of jobs in the presence of these multiple objectives. The motivation for this research arises from the good performance of the interactive man-machine scheduling systems in achieving significant levels of attainment in the set of objectives, simultaneously. We develop scheduling strategies similar to the man-machine approach in this research.
120676923
Preference Structure Representation Using Convex Cones in Multicriteria Integer Programming
A new efficient system of representing the decision-maker's preference structure in solving multicriteria integer programming problems is developed. The problem is solved by an interactive branch-and-bound method that employs the procedure of Zionts and Wallenius Zionts, S., J. Wallenius. 1983. An interactive multiple objective linear programming method for a class of underlying nonlinear utility functions. Management Sci.295. for multicriteria linear programming. The decision-maker's underlying utility function is assumed to be pseudoconcave, and his pairwise comparisons of decision alternatives are used to determine his preference structure in terms of certain convex cones in the objective function space and constraints on the weights on the objectives in the weight space. The two forms of preference structure representation are interrelated, and their underlying theory is developed. The primary objective of a representation scheme is exactness, and, in this respect, it is shown that the constraints on the weights are not adequate for representing nonlinear utility functions. On the other hand, the convex cones exactly represent any quasiconcave utility function and clearly avoid the approximations and inaccuracies in other utility assessment systems. Accordingly, an efficient ordered representation using convex cones is developed. An algorithmic framework for multicriteria integer programming that integrates the representation using convex cones with the branch-and-bound solution procedure is developed. Computational experience with bicriteria problems having up to 80 variables and 40 constraints is presented.
316216
The Distribution Problem with Carrier Service: A Dual Based Penalty Approach
The distribution problem with carrier service is an important optimization problem that often arises in vehicle routing. The problem arises in the distribution of commodities from a central facility to a set of geographically distributed locations. Each location has a certain demand, the distribution vehicle has a load capacity, and the entire operation should be completed within a certain time. An outside carrier is available for direct service of locations from the central facility. The problem is to determine a feasible tour for the company vehicle and the locations to be served by the outside carrier such that the total cost of the operations is minimized. We model this problem and develop a solution technique using valid inequalities. A key feature of the solution approach is that it can easily be extended to solve similar problems with any type and number of side constraints as encountered in the current model. The algorithm has been extensively tested and computational results for problems having u...
137267326
Thin Film Ferroelectric Materials and Devices
From the Publisher: 
Thin Film Ferroelectric Materials and Devices is a compilation of current research and development in two very important ferroelectric device technologies, namely ferroelectrics for Dynamic Random Access Memories (DRAM's) and Non-Volatile Ferroelectric Random Access Memories (NV-FRAM's). Given the rapid pace of development and the broad scope of the general topic of ferroelectric materials, readers will benefit from such a focused presentation. Thin Film Ferroelectric Materials and Devices will be of great value to materials and device scientists, device and process engineers, students, and postdoctoral associates. Furthermore, this compilation will serve as a concise introduction for new entrants to this exciting field.
10727206
A New Scheduling Algorithms For Real Time Tasks
The main objective of this paper is to develop the two different ways in which round robin architecture is modified and made suitable to be implemented in real time and embedded systems. The scheduling algorithm plays a significant role in the design of real time embedded systems. Simple round robin architecture is not efficient to be implemented in embedded systems because of higher context switch rate, larger waiting time and larger response time. Missing of deadlines will degrade the system performance in soft real time systems. The main objective of this paper is to develop the scheduling algorithm which removes the drawbacks in simple round robin architecture. A comparison with round robin architecture to the proposed architectures has been made. It is observed that the proposed architectures solves the problems encountered in round robin architecture in soft real time by decreasing the number of context switches waiting time and response time thereby increasing the system throughput.