5458806
Microcomputer based multiple criteria decision support system for strategic planning
Abstract There are two major approaches currently used for developing Decision support Systems (DSS) for strategic planning, especially in the objective formulation stage. Several mathematical models have been developed to abstract the decision situation. However, they do not take into account either behavioral aspects of decision making or the presence of multiple and conflicting objectives. A second approach is to consider the several qualitative factors that go into decision making; such considerations are normally situation-dependent and hence it is difficult to provide a system for general managerial situations. The Multiple Criteria Decision Making (MCDM) approach combines the advantages of both the approaches and, therefore, is an excellent alternative for designing DSS. This paper develops an MCDM approach to strategic planning. The model is applied to such a problem in a simulated environment and the problem is solved interactively. Our experience shows that the proposed methodology is a viable approach for solving practical decision problems in strategic planning.
13648716
EARS: An online bibliographic search and retrieval system based on ordered explosion
Abstract Ergonomics Abstracts Retrieval System (EARS) is an online bibliographic information search and retrieval system using the hierarchical subject classification of the Ergonomics Abstracts . EARS is designed using an inverted file organization and is implemented on CDC-Cyber. The data base of abstracts is organized using a fixed-length record format, where each logical record corresponds to a variable number of fixed-length physical records. Accordingly, an index for the identification of physical records from the logical records is used. The data base is inverted on a three-level hierarchical classification scheme and postings files are used for data base inversion. The data base is accessed after selectively traversing a 4-layer structure of indexes and postings files. EARS provides facilities to perform combinations of searches, limited searches, and certain editing functions. The system is currently used extensively by the Western New York Human Factors research community. The logical and physical designs of EARS, its interactive operational features, and its current expansions are described in this paper.
120648016
Theory of convex cones in multicriteria decision making
We develop the theory of convex polyhedral cones in the objective-function space of a multicriteria decision problem. The convex cones are obtained from the decision-maker's pairwise judgments of decision alternatives and are applicable to any quasiconcave utility function. Therefore, the cones can be used in any progressively articulated solution procedure that employs pairwise comparisons. The cones represent convex sets of solutions that are inferior to known solutions to a multicriteria problem. Therefore, these convex sets can be eliminated from consideration while solving the problem. We develop the underlying theory and a framework for representing knowledge about the decision-maker's preference structure using convex cones. This framework can be adopted in the interactive solution of any multicriteria problem after taking into account the characteristics of the problem and the solution procedure. Our computational experience with different multicriteria problems shows that this approach is both viable and efficient in solving practical problems of moderate size.
6732453
Enterprise computing environments and cost assessment
32066139
Topographically discounted Internet infrastructure resources: a panel study and econometric analysis
The Internet infrastructure is increasingly utilized for the provision and delivery of a variety of services. The rapid growth and substantial demand fluctuations of the supported services are placing strain on the service providers to effectively manage their infrastructure resources. Capacity Provision Network (CPN) is a market-driven mechanism that enables the service providers to efficiently allocate, share and trade service capabilities. Central to the operation of CPN is the notion of discounted capacities which capture the underlying topology of the Internet. It serves as a practical instrument for service providers to evaluate the utility of capacity services available at remote sites vis-à-vis the capacities available locally and from the content providers. We conducted an Internet based longitudinal field experiment to empirically assess and validate the critical properties of discount factors. Our analysis reveals that discount factors exhibit markedly lower volatility than network delays, and are more stable over seasonal and temporal trend patterns. The results related to size effects suggest that sharing and trade agreements with larger content can be particularly effective. Our finding on the existence of the concavity property points to the ability of intermediation services to enhance the overall gains from resource sharing arrangements.
62235624
An efficient approach to stochastic jobshop scheduling: algorithms and empirical investigations
Abstract Jobshop scheduling is one of the important classes of problems planning. The jobshop represents a common manufacturing environment, 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 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 considering 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 to the man-machine approach in this research. The algorithms developed in this research have been extensively tested and evaluated against the traditional scheduling methods using simulation studies. The results show that the proposed approach is efficient and viable for solving practical scheduling problems in the presence of multiple objectives.
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.
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.
46377078
A Portable Method of Integrating SLG Resolution into Prolog Systems
31851172
Automata-Driven Efficient Subterm Unification
Syntactic unification has widespread use in computing. There are several operations used in deductive computing such as critical pair generation, paramodulation and narrowing that require unifying a term s with every subterm of another term p. This subterm unification problem can be solved naively by repeatedly unifying s with each subterm of p in isolation. The drawback of doing unification in isolation is that commonality among subterms of p is ignored. We present an algorithm for efficient subterm unification by exploiting this commonality. The central idea used in our algorithm is to reduce the common part computation in unification into a string-matching problem and solve it efficiently using a string-matching automaton. The automaton succinctly captures the commonality between subterms of p. The string-matching approach, in conjunction with two new techniques called bidirectional-reduce and marking enables efficient unification of s with every subterm of p.
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.