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.
773323
Intelligent computer integrated manufacturing (I-CIM): Research perspectives
Abstract Manufacturing automation has progressed through various stages from simple data transfer to the intelligence-intensive systems. The future of CIM relies heavily on intelligence-intensive systems because manufacturing is no longer confined to one local site and manufacturing systems have become complex because of their global nature. In this article, the authors study the future manufacturing environment as a collaborative effort. The essential characteristics-the requirements for integration from a process and communication perspective-are identified as are steps in the process requiring further study. Finally, Intelligent-Computer Integrated Manufacturing (I-CIM) scenarios are presented for specific problems.
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.
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
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.
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.
100663548
La 0.5 Sr 0.5 CoO 3 electrode technology for Pb(Zr,Ti)O 3 thin film nonvolatile memories
Abstract Oxide electrode technology is investigated for optimization of Pb(Zr,Ti)O 3 (PZT) thin film capacitor properties for high density nonvolatile memory applications. PZT thin film capacitors with RF sputter deposited La 0.5 Sr 0.5 CoO 3 (LSCO) electrodes have been characterized with respect to the following parameters: initial dielectric hysteresis loop characteristics, fatigue performance, microstructure and imprint behavior. Our studies have determined that the fatigue of PZT capacitors with LSCO electrodes is less sensitive to B site cation ratio and underlying electrode stack technology than with RuO 2 electrodes. Doping PZT thin films with Nb (PNZT) improves imprint behavior of LSCO//PZT//LSCO capacitors considerably. We have demonstrated that PNZT 4/30/70 // LSCO capacitors thermally processed at either 550°C or 675°C have almost identical initial hysteresis properties and exhibit essentially no fatigue out to approximately 10 10 cycles.
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.
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.
10449411
Multistage Indexing Algorithms for Speeding Prolog Execution
In a previous article we proposed a new and efficient indexing technique that utilizes all the functors in the clause-heads and the goal. The salient feature of this technique is that the selected clause-head unifies (modulo nonlinearity)with the goal. As a consequence, our technique results in sharper discrimination, fewer choice points and reduced backtracking. A naı̈ve and direct implementation of our indexing algorithms considerably slowed down the execution speeds of a wide range of programs typically seen in practice. This is because it handled deep and shallow terms, terms with few indexable arguments, small and large procedures uniformly. To beneficially extend the applicability of our algorithms we need mechanisms that are ‘sensitive’ to term structures and size and complexity of procedures. We accomplish this in theν-ALS compiler by carefully decomposing our indexing process intomultiple stages . The operations performed by these stages increase in complexity ranging from first argument indexing to unification (modulo nonlinearity). Further the indexing process can be terminated at any stage if it is not beneficial to continue further. We have now completed the design and implementation of ν-ALS. Using it we have enhanced the performance of a broad range of programs typically encountered in practice. Our experience strongly suggests that indexing based on unification (modulo nonlinearity) is a viable idea in practice and that a broad spectrum of useful programs can realize all of its benefits.