Web-Books
in the Austria-Forum
Austria-Forum
Web-Books
Informatik
Algorithms for Scheduling Problems
Page - 169 -
  • User
  • Version
    • full version
    • text only version
  • Language
    • Deutsch - German
    • English

Page - 169 - in Algorithms for Scheduling Problems

Image of the Page - 169 -

Image of the Page - 169 - in Algorithms for Scheduling Problems

Text of the Page - 169 -

Algorithms 2018,11, 35 Definethecomplete transitionmatricesas Mˆ(1)(s)= ( pˆ(1)ij (s) ) N×N , s=0,1,2, . . . , with pˆ(1)ij (s)= p (1) j (s)+p (2) ij (s), i, j=1,2, . . . ,N, s=0,1,2, . . . (6) From(5)and(6) it followsthat Mˆ(1)(s)=ML(s)+M(2)(s), s=0,1,2. . . (7) p(2)j ( A(2)j (s) ) = N ∑ i=1 pi(s+1) ·p(2)ij (s), j=1,2, . . . ,N, s=0,1, . . . or p(2)j ( A(2)j (s) ) = N ∑ i=1 pi(s+1) ·p(2)ij (s), j=1,2, . . . ,N, s=0,1, . . . (8) In thematrix form,Equation(8)canberewrittenas p(2)(s)=p(s+1) ·M(2)(s), s=0,1, . . . (9) Thefollowingclaimis true. Claim. The followingrelationholds: N ∑ i=1 ( pi(s+1) · ( N ∑ j=1 p(2)ij (s) )) =1− N ∑ j=1 p(1)j (s), s=0,1, . . . (10) Theproof is straightforwardandskippedhere. 3. InformationEntropyasaMeasureofSupplyChainComplexity InformationentropyisdefinedbyShannonas follows[20].GivenasetofeventsE={e1, . . . , en} with apriori probabilities of event occurrenceP= {p1, . . . , pn}, pi≥ 0, such that pi + .. . +pn =1, theentropyfunctionH isdefinedby H=−∑I pi logpi. (11) Inorder toyieldallnecessary informationontheSCcomplexity issues, thispaperuses thedata recordingofall adverseeventsoccurred. Theenterprise is tocollect andstore thedataaboutmain adverseevents thatoccurredandledtoeconomic losses in theenterprise, compensationcost, aswell as the statistical analysisof the recordeddata. Such requirementalsoapplies to the registrationof informationaboutcontrolofcomplianceof targetandactualenvironmental characteristics. Similar to [12], foreachnodeu, consideran informationdatabasecalleda ‘riskprotocol’. This isa registration listofmost importantevents thathaveoccurred in thenodeduringapre-specifiedtime period. Theprotocolprovidesus the informationwhetherornot theeventsareundesirableand, in the lattercase,whatare its riskdriversandpossible losses. Thisdata is recordedintablesTBLu, representing listsofevents ineachnodeuduringacertain timeperiodT (e.g.,month,oryear). Eachrowinthetablecorrespondstoanindividualeventoccurring inagivennodeatacertain timemoment (forexample, aday).Weusesymbol f asan indexof risk drivers,Fas the totalnumberof riskdrivers,and rasan indexof theevent (row). Thevaluezrf at the intersectionofcolumn f androw r is equal to1 if the risk factor f is a sourceof theadverseevent r, and0—otherwise. The last column,F+1, ineachrow(r) contains themagnitudeofeconomic loss causedbythecorrespondingevent r. 169
back to the  book Algorithms for Scheduling Problems"
Algorithms for Scheduling Problems
Title
Algorithms for Scheduling Problems
Authors
Frank Werner
Larysa Burtseva
Yuri Sotskov
Editor
MDPI
Location
Basel
Date
2018
Language
English
License
CC BY 4.0
ISBN
978-3-03897-120-7
Size
17.0 x 24.4 cm
Pages
212
Keywords
Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
Categories
Informatik
Technik
Web-Books
Library
Privacy
Imprint
Austria-Forum
Austria-Forum
Web-Books
Algorithms for Scheduling Problems