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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
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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