We consider the computation of eigenvectors x = (x(1), . . . , x(n)) over the integers, where each component x(i) satisfies \x(i)\ less than or equal to b for an integer b. We address various problems in this context,...
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We consider the computation of eigenvectors x = (x(1), . . . , x(n)) over the integers, where each component x(i) satisfies \x(i)\ less than or equal to b for an integer b. We address various problems in this context, and analyze their computational complexity. We find that different problems are complete for the complexity classes NP, P-parallel to(NP), FNP//OptP[O(log n)], FPNP, P-NP and NPNP. Applying the results, finding bounded solutions of a Diophantine equation v . x(T) = 0 is shown to be intractable.
We consider the movement minimization problem in a conveyer flow shop processing controlled by one worker that has to serve all machines. Each machine can only execute tasks if the worker is present. A few jobs can be...
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We consider the movement minimization problem in a conveyer flow shop processing controlled by one worker that has to serve all machines. Each machine can only execute tasks if the worker is present. A few jobs can be queued in a buffer in front of each machine. The objective is to minimize the movement of the worker, which is how often the worker has to change the machines for the processing of all jobs. Such minimization problems usually appear in conveyer controlled manufacturing systems.
The STEM algorithm and Steuer's filtering procedure were offered to 142 subjects to assist them in solving six car buying problems of various complexity. Subjects could change between the algorithms and some other...
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The STEM algorithm and Steuer's filtering procedure were offered to 142 subjects to assist them in solving six car buying problems of various complexity. Subjects could change between the algorithms and some other program options almost at will. We show that the algorithms are evaluated differently and that objective measures of the solution process show differences between the algorithms that support subjective evaluations. If the objective task complexity is noticed (at least along one dimension: number of objective functions) we find that the choice of procedure varies with it as well as with subjective complexity evaluations. In general, STEM is favored by a minority of subjects, preferably for smaller sized problems. [ABSTRACT FROM AUTHOR]
We survey approximation algorithms for some well-known and very natural combinatorial optimization problems, the minimum set covering, the minimum vertex covering, the maximum set packing, and maximum independent set ...
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We survey approximation algorithms for some well-known and very natural combinatorial optimization problems, the minimum set covering, the minimum vertex covering, the maximum set packing, and maximum independent set problems;we discuss their approximation performance and their complexity. For already known results, any time we have conceived simpler proofs than those already published, we give these proofs, and, for the rest, we cite the simpler published ones. Finally, we discuss how one can relate the approximability behavior (from both a positive and a negative point of view) of vertex covering to the approximability behavior of a restricted class of independent set problems.
This study focuses on the impact of age, prior domain knowledge and cognitive abilities on performance, query production and navigation strategies during information searching. Twenty older adults and nineteen young a...
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This study focuses on the impact of age, prior domain knowledge and cognitive abilities on performance, query production and navigation strategies during information searching. Twenty older adults and nineteen young adults had to answer 12 information search problems of varying nature within two domain knowledge: health and manga. In each domain, participants had to perform two simple fact-finding problems (keywords provided and answer directly accessible on the search engine results page), two difficult fact-finding problems (keywords had to be inferred) and two open-ended information search problems (multiple answers possible and navigation necessary). Results showed that prior domain knowledge helped older adults improve navigation (i.e. reduced the number of webpages visited and thus decreased the feeling of disorientation), query production and reformulation (i.e. they formulated semantically more specific queries, and they inferred a greater number of new keywords). (C) 2016 Elsevier Ltd. All rights reserved.
Irrefutable evidence shows that greater openness toward external partners enhances a firm's ability to solve innovation-related problems. To manage open innovation (OI) projects, firms use a variety of governance ...
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Irrefutable evidence shows that greater openness toward external partners enhances a firm's ability to solve innovation-related problems. To manage open innovation (OI) projects, firms use a variety of governance modes, including market-based contracts, platform intermediaries, and equity and non-equity partnerships. While innovation projects can be very diverse and characterized by various attributes, such as complexity and knowledge hiddenness, only a few conceptual studies have hitherto considered project attributes as drivers of OI governance mode selection. Using a sample of 85 OI projects and a set of illustrative cases, this article explores empirically how project attributes influence OI governance mode selection. This empirical study advances previous conceptual work on OI governance. By accounting for project-level heterogeneity, we explore the microfoundations of OI and provide more stable and fundamental insights into OI governance than previous industry- and firm-level analyses did. In addition, we suggest that effective OI management depends on matching project attributes with the benefits and costs of specific governance modes. Finally, we argue that this study enhances understanding and conceptualization of the relationship between project complexity and decomposability in the context of OI.
This paper proposes a problem transformation method, called feedback transformation method, for solving the planning problems. Some basic notions from the theory of problem transformation are introduced. Two measures ...
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This paper proposes a problem transformation method, called feedback transformation method, for solving the planning problems. Some basic notions from the theory of problem transformation are introduced. Two measures of problem complexity are defined. Algebraic properties of the feedback transformation are investigated. Finally, a partial relationship between the problem transformation and decomposition methods is established.
For Mealy and Moore automata over a finite commutative-associative ring with unity, which transition function is defined by nonlinear equations of the second degree, and the output function is affine and linear map of...
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For Mealy and Moore automata over a finite commutative-associative ring with unity, which transition function is defined by nonlinear equations of the second degree, and the output function is affine and linear map of the states set, respectively, the problem of reconstruction of the initial state vector is solved. The case, when this problem is trivial, is considered. It is found that in other cases the problem is difficult. It is found that the property "to be reversible automaton" generally does not affect the complexity of solving the problem of reconstruction of the initial state vector for the investigated automata.
In this paper we investigate the role that the competition among knowledge sources plays in the problem solving behavior of a population as the complexity of the optimization problem solving landscapes increases. We e...
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In this paper we investigate the role that the competition among knowledge sources plays in the problem solving behavior of a population as the complexity of the optimization problem solving landscapes increases. We employ a type of game theoretic mechanism, auctions, in our study. Our main goal is to determine whether it matters if knowledge sources competed for individuals using auction mechanisms or weighted majority win mechanisms as the landscape complexity increased. The weighted majority win situation allows the Knowledge Sources to make predictions about future success whereas the Auction mechanism allows them to invest in their future by using tokens earned from recent performance. This latter approach allows contextual Knowledge Sources such as Situational Knowledge to play a larger role. Although the results are preliminary, it appears that the auction mechanism is more efficient when solving a problem in situations where contextual information is available. In that case, it is easier for the knowledge sources to make judicial bids or investments. However, once the landscapes become chaotic there is less contextual information available and correspondingly little advantage to the auction mechanism over the weighted majority win situation in terms of the number of generations needed to achieve a solution.
We consider the combinatorial stack-up problem motivated by stacking up bins from a conveyor onto pallets. The stack-up problem is to decide whether a given list q of labeled objects can be processed by removing step ...
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We consider the combinatorial stack-up problem motivated by stacking up bins from a conveyor onto pallets. The stack-up problem is to decide whether a given list q of labeled objects can be processed by removing step by step one of the first s objects of q so that the following holds. After each removal there are at most p labels for which the first object is already removed from q and the last object is still contained in q. We give some NP-completeness results and we introduce and analyze a polynomial time approximation algorithm for the stack-up problem.
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