399
requestedurgentmedicalassistanceforpassengersor
crewmembers,Ro‐Paxshipcanentryinportearlier,
because in usual conditions port terminals are not
ready for mooring of ships and provide cargo
handlingorpassengerembankmentoperations.
In some cases it is possible to use maximal
distributionmethodfor
theRo‐Paxshipsarrivaldelay
calculation. Main dependence could be expressed as
follows[14]:
max min
'
AV n
TT kPT
(6)
where:
AV
T ‐ average Ro‐Pax ship’sarrival time, can
be taken as
yi
m
;
n
k
‐coefficient depends on the
numberofdata,incase,ifnumberofdataare3–this
coefficientwillbe‐0,55;incasenumberofdata4‐
thiscoefficientwillbe0,47andsimilardependsofthe
datanumber:5–0,43;6–0,395;7–0,37;8–
0,351;9–
0,337;10–0,329;11–0,325;12–0,322andsoon,but
minimum of this coefficient could be about 0,315 in
case number of data will be more as 15.
'
‐
probability dependence coefficient (in case of this
coefficient1–probabilitywillbe68,3%,incaseof
thecoefficient2–probabilitywillbe95,3%,incaseof
thiscoefficient3–probabilitywillbe99,7%);
max min
T
‐differencebetweenminimumandmaximumresults,
that means between earliest and latest Ro‐Pax ships
arrivaltime.
As the case study of Ro‐Pax ships arrival time
delay evaluation were taken Ro‐Pax shipping lines
Klaipeda–KielandKlaipeda–Karlshamn.BothRo‐
Paxshippinglinesaredaily,just
sailingtime to one
directionontherouteKlaipeda–Kieltakesabout20
hoursandtimeinporttakesabout4hoursandonthe
routeKlaipeda–Karlshamnsailingtimetakesabout
14 hours and shipʹs stay at the port takes about 10
hours. Analysis covers few
months during summer
timeingoodweatherconditionsandinwintertime,
whenweatherconditionsweremorecomplicated.
Inwinter andsummer time wereexcludedstorm
days,whenwindwasmorethan20m/sandRo‐Pax
ships cannot entry into the port or leave port
according to the schedule. In
total were taken more
than 100 arrivals and received next results:
mathematical hope of the Ro‐Pax ships on line
Klaipeda–Kieltoportarrivaldelaywas17minutes,
andon line Klaipeda –Karlshamn‐was21 minutes
anddispersionsoraveragecircleerrorreceived+/‐8
minutesfor
theRo‐PaxlineKlaipeda–Kieland+/‐6
minutesfortheRo‐PaxlineKlaipedaKarlshamn.
According to maximal distribution method was
taken probability 68,3 %, coefficient depends on the
number of data was taken 0,315, and difference
betweenminimumandmaximumresultsfortheRo‐
PaxlineKlaipeda
–Kielwasreceived62minutes,for
theRo‐PaxlineKlaipeda‐Karlshamnwasreceived51
minutes.
Average Ro‐Pax ship’s arrival delay time for the
Ro‐PaxlineKlaipeda–Kielwasreceived17minutes
incomparisonwithtimetableandfortheRo‐Paxline
Klaipeda – Karlshamn
was received 12 minutes in
comparison with the schedule. Finally according to
maximaldistributionmethodRo‐Paxshipsdelaytime
for the line Klaipeda –Kiel was 36 minutes and for
theRo‐Paxline Klaipeda –Karlshamn–28 minutes.
Differences between evaluation methods based on
different density, because in
dispersion method
density of the results is similar in all received time
pass and in maximal distribution method density is
differentonreceivedtimepass.
Next important problem, which is necessary to
solve: sustainable information system, which has be
useful for ports, terminals and clients, that means
accurateinformationfor
passengersandtruckdrivers,
because it links with city limitations to use some
streetsinrushhoursfortheheavytransportsdriving
toandfromportterminals.
3.2 Graphtheorypossibilitiesoptimizefreightand
passengerstransportrichRo‐Roterminals
ThisproblemfortherichRo‐Roterminalinport via
cities during rush hours can be solved on basis of
graph theory. For developing an optimal streets
network,which arenotbusyduring rush hoursand
couldbeusedfortheheavytransport.Theapplication
ofgraph theorymethodis used,wherethemodelis
buildinthatincorporatesa
setofvertices,whichare
representing permit streets cross places and a set of
edges,whichrepresentsthedistancesbetweenpermit
streetscrossingpoints.Theoptimalpermitstreetsfor
heavytransportsduringrushhoursnetworkmodeled
asagraphisexpressedasfollows[6,8]:
(, )GVE
, (7)
where:V‐thesetofvertices;E‐thesetofedges.
As an example, the permit streets network could
becreatedinKlaipedacity streetsnetwork,whichis
notbusyduringrushhours,asshownonFigure4.
Figure4. Not busy streets network in rush hours as the
graphtree
Forthegraphtree,presentedonfigure4,thesets
of vertices and the set of edges can be expressed as
follows[1,4,9]:
123456
,,,,,Vvvvvvv
(8)
12 23 24 25 56
( , )( , )( , )( , )( , )E vvvvvvvvvv
(9)