From e6be2ca5af9f51fb10d7e00da1e10a809b901a1a Mon Sep 17 00:00:00 2001 From: "Jip J. Dekker" Date: Thu, 29 Jul 2021 19:29:08 +1000 Subject: [PATCH] Add acronyms to glossary entries --- assets/acronyms.tex | 2 +- assets/glossary.tex | 24 ++++++++++++------------ 2 files changed, 13 insertions(+), 13 deletions(-) diff --git a/assets/acronyms.tex b/assets/acronyms.tex index 19e133e..c935ff4 100644 --- a/assets/acronyms.tex +++ b/assets/acronyms.tex @@ -14,7 +14,7 @@ \newacronym[see={[Glossary:]{gls-cp}}]{cp}{CP\glsadd{gls-cp}}{\emph{Constraint Programming}} -\newacronym[see={[Glossary:]{gls-cse}}]{cse}{CSE\glsadd{gls-cse}}{Common Sub-expression Elimination} +\newacronym[see={[Glossary:]{gls-cse}}]{cse}{CSE\glsadd{gls-cse}}{\emph{Common Sub-expression Elimination}} \newacronym{cnf}{CNF\glsadd{cnf}}{\emph{Conjunctive Normal Form}} diff --git a/assets/glossary.tex b/assets/glossary.tex index 71028c5..3d3525f 100644 --- a/assets/glossary.tex +++ b/assets/glossary.tex @@ -29,7 +29,7 @@ } \newglossaryentry{gls-ast}{ - name={Abstract Syntax Tree}, + name={Abstract Syntax Tree (AST)}, description={A tree structure representing the syntactic structure of a piece of computer language. These structures are often used in a \gls{compiler} or \gls{interpreter}.}, } @@ -97,12 +97,12 @@ } \newglossaryentry{gls-cbc}{ - name={COIN-OR Branch-and-Cut}, + name={COIN-OR Branch-and-Cut (CBC)}, description={A well-known open source \gls{mip} \gls{solver} \autocite{forrest-2020-cbc}.}, } \newglossaryentry{gls-cbls}{ - name={constraint-based local search}, + name={constraint-based local search (CBLS)}, description={A form of local search using \gls{constraint} violations as its \gls{objective}. The search method estimate the amount a \gls{constraint} is \gls{violated} in terms of a numeric value, the objective of the search is to minimize this value. Generally \constraints{} can also offer ``search steps'' that can be taken that do not introduce new violations.}, } @@ -152,17 +152,17 @@ } \newglossaryentry{gls-chr}{ - name={constraint handling rules}, + name={constraint handling rules (CHR)}, description={A non-deterministic declarative rule based programming language to maintain or improve a constraint store. Constraint handling rules are often used as an extension of \gls{clp}. See \cref{sub:back-chr}.}, } \newglossaryentry{gls-clp}{ - name={constraint logic programming}, + name={constraint logic programming (CLP)}, description={An extension of logic programming to include the concepts of \gls{cp}. A constraint logic program manipulates a \gls{constraint} store to find relevant variants where all \glspl{constraint} contained in the store are \gls{satisfied}. See \cref{subsec:back-clp}.}, } \newglossaryentry{gls-cp}{ - name={constraint programming}, + name={constraint programming (CP)}, description={ A general technique to find \glspl{sol} to \glspl{instance} of \glspl{model}. A constraint programming solver interleaves \gls{propagation} with making \glspl{search-decision} to reduce the \gls{search-space}. @@ -171,7 +171,7 @@ } \newglossaryentry{gls-cse}{ - name={common sub-expression elimination}, + name={common sub-expression elimination (CSE)}, description={A technique stemming from programming languages to avoid duplicate computation. In \glspl{cml} this technique is used to avoid the creation of duplicate \glspl{variable} and \glspl{constraint}. See \cref{subsec:back-cse}.}, } @@ -344,12 +344,12 @@ } \newglossaryentry{gls-lcg}{ - name={lazy clause generation}, + name={lazy clause generation (LCG)}, description={Types of \gls{solver} that extend \gls{cp} solving with \gls{sat} capabilities. Lazy clause generation \glspl{solver} lazily translate a \gls{cp} model for a \gls{sat} backend. As such, they maintain the pruning ability of a \gls{cp} solver while gaining the ability of \gls{sat} solvers to explain any failures in the search.}, } \newglossaryentry{gls-lns}{ - name={large neighbourhood search}, + name={large neighbourhood search (LNS)}, description={ A \gls{meta-optimization} strategy that repeatedly reduces the \gls{search-space} by applying different \glspl{neighbourhood} often based on a previous \gls{sol}. Large neighbourhood search is a well-known method to quickly improve a \gls{sol}. Large neighbourhood search is not guaranteed to find the \gls{opt-sol} and if it does, then it will be unable to prove that it did. } @@ -402,12 +402,12 @@ } \newglossaryentry{gls-maxsat}{ - name={Maximum Satisfiability}, + name={Maximum Satisfiability (MaxSAT)}, description={An extension of the \gls{gls-sat} problem class into an \gls{opt-prb}. A \gls{gls-sat} problem in \gls{gls-cnf} is extended with weights for each clause. An \gls{opt-sol} of a problem \instance{} maximizes the weights of the \gls{satisfied} clauses.}, } \newglossaryentry{gls-mip}{ - name={mixed integer programming}, + name={mixed integer programming (MIP)}, description={ A solving technique that tries to find the \gls{opt-sol} for a \cmodel{} containing a mixture of Integer and floating point \glspl{variable} subject to \glspl{constraint} in the form of linear (in-)equations. Mixed integer programming is extensively studied and there are many successful \glspl{solver} dedicated to solving mixed integer programs. @@ -493,7 +493,7 @@ } \newglossaryentry{gls-sat}{ - name={Boolean satisfiability}, + name={Boolean satisfiability (SAT)}, description={ A problem class that tries to find a valid \gls{assignment} for a set of Boolean \glspl{variable} subject to a logical formula. Boolean satisfiability is extensively studied and there are many \glspl{solver} dedicated to solving this problem class.