From 09d7c85a44c07040d164d8293593fdb84fc9bba7 Mon Sep 17 00:00:00 2001 From: Martin Mares Date: Sat, 12 May 2007 12:16:11 +0200 Subject: [PATCH] Pridana prvni verze kapitoly o grafovych algoritmech. --- 8-grafy/8-grafy.tex | 271 +++++++++++++++++++++++++++++++++++++++ 8-grafy/Makefile | 3 + 8-grafy/img1_stvorec.eps | 121 +++++++++++++++++ 8-grafy/img2_dfs.eps | 211 ++++++++++++++++++++++++++++++ 8-grafy/img3_dfs.eps | 264 ++++++++++++++++++++++++++++++++++++++ 8-grafy/img4_susedia.eps | 245 +++++++++++++++++++++++++++++++++++ 8-grafy/img5_dfso.eps | 259 +++++++++++++++++++++++++++++++++++++ 8-grafy/img6_BFS.eps | 223 ++++++++++++++++++++++++++++++++ 8-grafy/img7_hrany.eps | 179 ++++++++++++++++++++++++++ 8-grafy/img8_kvz.eps | 165 ++++++++++++++++++++++++ all/Makefile | 2 +- 11 files changed, 1942 insertions(+), 1 deletion(-) create mode 100644 8-grafy/8-grafy.tex create mode 100644 8-grafy/Makefile create mode 100644 8-grafy/img1_stvorec.eps create mode 100644 8-grafy/img2_dfs.eps create mode 100644 8-grafy/img3_dfs.eps create mode 100644 8-grafy/img4_susedia.eps create mode 100644 8-grafy/img5_dfso.eps create mode 100644 8-grafy/img6_BFS.eps create mode 100644 8-grafy/img7_hrany.eps create mode 100644 8-grafy/img8_kvz.eps diff --git a/8-grafy/8-grafy.tex b/8-grafy/8-grafy.tex new file mode 100644 index 0000000..2feed6d --- /dev/null +++ b/8-grafy/8-grafy.tex @@ -0,0 +1,271 @@ +\input mjmac.tex +\input lecnotes.tex +\input epsf.tex + +\prednaska{8}{Základní grafové algoritmy}{(Zapsali M. Petr, O.Tichý, ¥. Magic)} + +\h{Reprezentace grafu} +Oznaème vrcholy grafu na následujícím obrázku písmeny A, B, C, D. +Pokud bychom chtìli tento graf uchovat v pamìti poèítaèe, máme na výbìr +hned nìkolik zpùsobù, jak to udìlat. +\figure{img1_stvorec.eps}{}{\epsfxsize} + +\s{1. seznam hran} + +Jednodu¹e vypí¹eme seznam v¹ech dvojic vrcholù grafu spojených hranou. + +AB, BC, DC, CA, BC +\medskip + +\s{2. matice sousednosti} + +Matice sousednosti je pole $A$ o velikosti $n \times n$, jeho¾ prvky na +souøadnicích $i, j$ jsou dány následujícím pøedpisem: + +$$ A_{i,j} = \left\{ \matrix {0 \Leftrightarrow \{i,j\} \notin E \cr + 1 \Leftrightarrow \{i,j\} \in E \cr + } +\right.$$ + +Ná¹ graf z obrázku vý¹e by tedy v maticové reprezentaci vypadal takto: + +$$\bordermatrix{ + & A & B & C & D\cr +A & 0 & 1 & 1 & 0\cr +B & 1 & 0 & 1 & 1\cr +C & 1 & 1 & 0 & 1\cr +D & 0 & 1 & 1 & 0\cr +}$$ + +S touto matici se pracuje velmi snadno (napø. v¹echny sousedy i-tého vrcholu +zjistíme jednodu¹e tak, ¾e projdeme i-tý øádek matice, co¾ pøedstavuje èasovou +slo¾itost $O(n)$), ale má i jednu zøejmou nevýhodu: její velikost je v¾dy +kvadratická bez ohledu na to, jak "øídký" je graf. U grafu s mnoha vrcholy, ale +s malým poètem hran, tedy budeme zbyteènì plýtvat místem v pamìti. + +Nabízí se proto tøetí, úspornìj¹í, zpùsob, a to: +\medskip + +\s{3. seznam sousedù} + +%$$\matrix{ +%A&\rightarrow&BC\quad \cr +%B&\rightarrow&ACD\cr +%C&\rightarrow&ABD\cr +%D&\rightarrow&BC\quad \cr +%}$$ + +V pamìti poèítaèe by se dal seznam sousedù uchovávat dvìma poli: polem vrcholù +$V$ grafu, jeho¾ prvky postupnì pro ka¾dý vrchol udávají index na zaèátek +odpovídajícího úseku v poli $E$, ve kterém by byli ulo¾eni jeho sousedé. +\figure{img4_susedia.eps}{Znázornìní polí seznamu sousedù.}{\epsfxsize} + +Na tuto reprezentaci u¾ staèí prostor $O(n + m)$, co¾ u¾ je, na rozdíl od +pøedchozího kvadratického prostoru, docela pøíjemné. + +Je¹tì dodejme, ¾e aèkoliv jsme jednotlivé reprezentace ukazovali na pøíkladì +neorientovaného grafu, orientované grafy se dají reprezentovat prakticky stejnì. U +orientovaných grafù je toti¾ jediný rozdíl: existuje-li hrana z vrcholu $u$ do +vrcholu $v$, neznamená to, ¾e existuje i hrana z $v$ do $u$ (tedy $(u, v)$ a $(v, u)$ +tvoøí uspoøádané dvojice). + +\h{Prùchod grafem} + +\s{Definice:} Vrchol je dosa¾itelný, pokud do nìj vede cesta z poèáteèního vrcholu. + +\s{Efektivní prùchod by mìl splòovat tyto podmínky:} +\itemize\ibull +\:ka¾dou hranu projdu právì jednou (resp. maximálnì dvakrát - 1x tam, 1x zpìt) +\:hranou se vracím zpìt, a¾ kdy¾ u¾ z vrcholu, na kterém momentálnì jsem, nevede + dosud neprozkoumaná hrana +\:pokud jsem do¹el po hranì do ji¾ døíve nav¹tíveného vrcholu, hned se vrátím +\endlist + +\s{Koneènost} + +\proof +Plyne z prvního bodu. +\qed + +\s{Korektnost} (algoritmus projde celý graf) + +\proof +Sporem: Nech» existuje vrchol, který je dosa¾itelný, ale algoritmus ho nepro¹el. +Pak jsme ale pøi prùchodu narazili na $\{u, v\}\in E$ takovou, ¾e vrchol $u$ je +dosa¾itelný a $w$ dosa¾itelný není. Tzn., ¾e $\{u, w\}$ tvoøí neprozkoumanou +hranu $\Rightarrow$ spor s druhým bodem. +\qed + +\s{Èasová slo¾itost} + +Z toho, ¾e ¾ádná hrana ani vrchol se neprojde vícekrát (první podmínka +efektivního prùchodu), plyne èasová slo¾itost $O(n + m)$. + +\>Nyní si nìco povíme o dvou zpùsobech, kterak mù¾eme procházet grafy. + +\s{Prùchod do hloubky} (Depth First Search, DFS) + +Prùchod do hloubky je prvním základním postupem pøi procházení grafem. Pokud bychom +chtìli DFS trochu pøiblí¾it, mohli bychom ho pøirovnat k Théseovì postupu +pøi prùchodu Minotaurovho bludi¹te za pomoci Ariadniny nitì. + +\s{Prùchod do ¹íøky} (Breadth First Search, BFS) + +Na rozdíl od prohledávání do hloubky vyu¾ívá prohledávání do ¹íøky namísto zásobníku +frontu. Motivaèní úlohou by mohlo být napø. hledání nejkrat¹í cesty mezi dvìma vrcholy +v grafu, nebo známý pøevozníkùv problém. +\figure{img6_BFS.eps}{}{\epsfxsize} + +\s{Pø.} Koza, vlk a zelí +\figure{img8_kvz.eps}{}{\epsfxsize} + +Øe¹ení ulohy by se dalo popsat jako hledání cesty grafem stavù od poèáteèního stavu +(koza, vlk i zelí jsou na jednom bøehu) do koncového (v¹ichni byli bez újmy pøevezeni +na druhý bøeh øeky). + +\h{DFS na neorientovaném grafu} + +Pøi prùchodu grafu do hloubky pou¾íváme zásobník. Na zaèátku se v nìm nachází pouze +vstupní vrchol v. Dokud není zásobník prázdný, tak z nìj odebíráme vrchol; ten oznaèíme +jako zpracovaný (abychom ho v budoucnu, kdybychom na nìj je¹tì nìkdy narazili, +nezpracovávali znovu) a do zásobníku pøidáme v¹echny jeho sousedy takové, kteøí +je¹tì nebyli oznaèeni jako zpracovaní. + +\>Vrcholy znaèíme tìmito barvami +\itemize\ibull +\:bílá - dosud nenav¹tívìné vrcholy (na zaèátku jsou tedy bílé v¹echny) +\:¹edá - oznaèuje právì zpracovávaný vrchol +\:èerná - u¾ zpracované vrcholy +\endlist + +\>U ka¾dého vrcholu si dále také zapamatujeme èas pøíchodu a èas odchodu +($in[v]$, $out [v]$). + +\s{Algoritmus} + +\algo +\:procedure Projdi(v) +\::color[v] := ¹edá +\::time := time + 1 +\::in[v] := time +\::$\forall$ w $\in$ Sousedi(v): +\:::if color[w] = bílá $\Rightarrow$ +\::::Projdi(w) +\::color[v] := èerná +\::time := time + 1 +\::out[v] := time +\:: +\:procedure DFS() +\::$\forall$ v: color[v] := bílá +\::time := 0 +\::$\forall$ v $\in$ V : +\:::if color[v] = bílá $\Rightarrow$ +\::::Projdi(v) +\endalgo + +Implementaci zásobníku jsme v tomto meta-algoritmu nahradili pou¾itím rekurze +(která ale funguje na podobném principu, kdy se na zásobník vkládají jednotlivá +volání rekurzivní funkce). + +Na následujících obrázcích je znázornìno, jak probíhá prùchod grafu pomocí DFS: + +\figure{img2_dfs.eps}{}{\epsfxsize} +\figure{img3_dfs.eps}{Znázornìní prùbìhu algoritmu.}{\epsfxsize} + +\s{Hrany v tomto znázornìní dìlíme na:} +\itemize\ibull +\:stromové - v momentì prùchodu vedou do dosud nenav¹tíveného, bílého, vrcholu +\:zpìtné - ostatní hrany +\endlist + +\s{Pozorování:} plné hrany tvoøí strom (DFS strom, strom prùchodu do hloubky). + +\s{Aplikace:} +\item{(1)} hledání kostry +\item{(2)} hledání komponent souvislosti + +Èasová slo¾itost tìchto aplikací DFS je stejná jako slo¾itost pùvodního +meta-algoritmu, tedy $O(n + m)$. + +\item{(3)} hledání artikulací + +Tuto aplikaci si teï rozebereme tro¹ku podrobnìji. Nejprve v¹ak nìkolik definic. + +\s{Definice:} Artikulace je vrchol v grafu, jeho¾ odebráním se graf rozpadne na alespoò +dvì komponenty souvislosti. + +\s{Definice:} Most je hrana v grafu, jejím¾ odebráním se graf rozpadne na dvì +komponenty souvislosti. + +\s{Pozorování}: Most je taková hrana, její¾ oba koncové vrcholy jsou artikulacemi. + +\s{Definice:} Graf je 2-souvislý, jestli¾e po odstranìní libovolného vrcholu +zùstane souvislý. + +\s{Definice:} 2-souvislá komponenta je maximální 2-souvislý podgraf. + +Jak bychom tedy pøi hledání artikulací v grafu mohli postupovat? Jako první +se nabízí tento algoritmus: + +\s{Hloupý algoritmus} + +Berme si postupnì v¹echny vrcholy grafu; pro ka¾dý zjistíme, jestli se jeho +odebráním zvý¹il poèet komponent. K tomu bychom mohli pou¾ít prùchod do hloubky, +který jsme si u¾ ukázali. Procedura Projdi(v) projde a oznaèí v¹echny vrcholy +dosa¾itelné z v, tedy v¹echny vrcholy komponenty obsahující vrchol v. Mù¾eme +tedy udìlat takovou zmìnu, ¾e si budeme nav¹tívené vrcholy oznaèovat èíslem +komponenty. + +Takový algoritmus by mìl slo¾itost $n \times O(n + m))$ (pro ka¾dý vrchol grafu +bychom n-krát spou¹tìli DFS), co¾ se nám vùbec nelíbí. Pokusme se tedy najít +nìco lep¹ího. Nejprve uèiòmì toto pozorování: + +\s{Pozorování:} v je artikulace $\Leftrightarrow$ v je koøen DFS stromu a má +alespoò dva potomky nebo v není koøen a má syna w takového, ¾e ze ¾ádného +jeho potomka nevede hrana do pøedchùdce v. + +\s{Definice:} Pøípustná cesta je taková cesta, pokud vede pøes stromové hrany +DFS stromu (mù¾e konèit i skokem zpìt). + +\figure{img7_hrany.eps}{Pøíklady pøípustných cest.}{\epsfxsize} + +\>Dále si definujme funkci low pro ka¾dý vrchol v, takto: + +\s{low(v)} = min(in[w], z v do w vede pøípustná cesta) + +\s{Pozorování:} v je artikulace $\Leftrightarrow$ v je koøen DFS stromu a má +alespoò dva potomky nebo má syna w takového, ¾e platí $low(w) \geq in[w]$. + +\s{Jak ale hodnotu funkce low(w) spoèítat?} + +low(v) = min(x, y, z) + +x = in[v] + +y = min(in[w], $\{w, v\}$ je zpìtná hrana) + +z = min(low(w), $\{v, w\}$ je stromová hrana) + +\h{DFS na orientovaném grafu} + +\figure{img5_dfso.eps}{Graf a znázornení prùbehu:}{\epsfxsize} + +\s{Hrany v dìlíme na: } +\itemize\ibull +\:stromové $\{A,B\}$, $\{B,C\}$, $\{B,D\}$ +\:zpìtné: vedou do pøedchùdce v DFS stromì (do ¹edého vrcholu) +\:pøíèné: vedou do vrcholu v jiném podstromì (do èerného vrcholu) +\:dopøedné: vedou do svého potomka (do èerného vrcholu v tém¾e podstromì) +\endlist +\bigskip + +\>Na závìr nìkolik \s{pozorování:} + +Intervaly (in[v], out[v]) $\forall v \in V $ tvoøí dobré uzávorkování. + +v je následník u $\Leftrightarrow (in[v], out[v]) \leq (int[u], out[u]) $ + +$\{u,v\}$ je zpìtná hrana $\Leftrightarrow (in[u], out[u]) \leq (in[v], out[v])$ + +$\{u,v\}$ je pøíèná hrana $\Leftrightarrow int[v] < out[v] < in[u] < out[u]$ +\bye diff --git a/8-grafy/Makefile b/8-grafy/Makefile new file mode 100644 index 0000000..fce3887 --- /dev/null +++ b/8-grafy/Makefile @@ -0,0 +1,3 @@ +P=8-grafy + +include ../Makerules diff --git a/8-grafy/img1_stvorec.eps b/8-grafy/img1_stvorec.eps new file mode 100644 index 0000000..13e4481 --- /dev/null +++ b/8-grafy/img1_stvorec.eps @@ -0,0 +1,121 @@ 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