172,440 research outputs found
Abstract State Machines 1988-1998: Commented ASM Bibliography
An annotated bibliography of papers which deal with or use Abstract State
Machines (ASMs), as of January 1998.Comment: Also maintained as a BibTeX file at http://www.eecs.umich.edu/gasm
Several types of types in programming languages
Types are an important part of any modern programming language, but we often
forget that the concept of type we understand nowadays is not the same it was
perceived in the sixties. Moreover, we conflate the concept of "type" in
programming languages with the concept of the same name in mathematical logic,
an identification that is only the result of the convergence of two different
paths, which started apart with different aims. The paper will present several
remarks (some historical, some of more conceptual character) on the subject, as
a basis for a further investigation. The thesis we will argue is that there are
three different characters at play in programming languages, all of them now
called types: the technical concept used in language design to guide
implementation; the general abstraction mechanism used as a modelling tool; the
classifying tool inherited from mathematical logic. We will suggest three
possible dates ad quem for their presence in the programming language
literature, suggesting that the emergence of the concept of type in computer
science is relatively independent from the logical tradition, until the
Curry-Howard isomorphism will make an explicit bridge between them.Comment: History and Philosophy of Computing, HAPOC 2015. To appear in LNC
Solution Repair/Recovery in Uncertain Optimization Environment
Operation management problems (such as Production Planning and Scheduling)
are represented and formulated as optimization models. The resolution of such
optimization models leads to solutions which have to be operated in an
organization. However, the conditions under which the optimal solution is
obtained rarely correspond exactly to the conditions under which the solution
will be operated in the organization.Therefore, in most practical contexts, the
computed optimal solution is not anymore optimal under the conditions in which
it is operated. Indeed, it can be "far from optimal" or even not feasible. For
different reasons, we hadn't the possibility to completely re-optimize the
existing solution or plan. As a consequence, it is necessary to look for
"repair solutions", i.e., solutions that have a good behavior with respect to
possible scenarios, or with respect to uncertainty of the parameters of the
model. To tackle the problem, the computed solution should be such that it is
possible to "repair" it through a local re-optimization guided by the user or
through a limited change aiming at minimizing the impact of taking into
consideration the scenarios
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