CONTAINER
Terminals Modeling
Nam-Kyu Park
Professor
Tongmyong University,
Department of Logistics
Management
Branislav Dragović
Associate Professor
University of Montenegro,
Maritime Faculty
Necessity of Simulation in Terminal Planning
 Container terminal is critical node for logistics flow, but sometimes it does
not follow shipping company request like more berths, deep sea, tandem QC,
automation and quick administration etc.
 The crucial terminal management problem is to optimize the balance
between the shipowners who request quick service of their ships and
economic use of allocated resources.
 Proper performance measurement of terminal is vital issue in modern
container terminal planning
 Simulation modeling technique
−
widely used in the analysis of port and terminal planning process and
container handling system
−
used as an important tool for decision-making in planning a shipberth linkage design and modeling
Table 1: Literature review of a container port and
ship-berth link planning by using simulation
Considered
problems
Simulation of
container
terminals (CT)
and ports
Approaches
Modsim III
Object oriented programming, C++
ARENA
ARENA, SLX
Visual SLAM
AweSim
Witness software
Taylor II
GPSS/H
Extend-version 3.2.2
Scenario generator
Overview
concept
Quantitative models for various
decision problems in CT
Logistics processes and operations
in CT – optimization methods
References
Gambardella et al., 1998;
Yun and Choi, 1999;
Tahar and Hussain, 2000;
Merkuryeva et al.;
Legato and Mazza, 2000;
Nam et al., 2002; Demirci, 2003;
Shabayek and Yeung, 2002;
Kia et al., 2002;
Pachakis and Kiremidjian, 2003;
Dragovic et. al. (2005a and 2005b);
Sgouridis et al., 2003;
Hartmann, 2004;
Vis and Koster, 2003;
Steenken, et al., 2004.
There are few studies dealing with ship-berth link planning. Researches
related to a container port and particularly ship-berth link planning,
which use simulation, are summarized in Table 1.
Model development approach
 The simulation model covers both the quay and CY, thus becoming a
integration model between the quay and CY.
 The operation unit in the quay is a ship, but the operation unit in the CY
is a container.
 Accordingly, author has developed independently both a quay
performance analysis model and a CY performance analysis model with
ARENA, and then has combined these two models into an integrative
simulation model.
Figure 1. Operation procedure on ship-berth link
Ship-berth link is complex due to different interarrival times of ships, different dimensions of ships,
multiple quays and berths, different capabilities of QC and so on. The modeling of these systems
must be divided into several segments, each of which has its own specific input parameters. These
segments are closely connected with the stages in ship service presented in Figure 1.
 Flow of quay simulation model
Ship arrival
LPC by ship
Berth allocation
C/C assignment by berth
Loading and unloading
Ship departure
CY allocation
CY Simulation Model
 3 types of container cargoes: export container cargo, import container
cargo, and transshipment cargo.


At the time of ship berthing, first of all, import container cargoes is
to be unloaded, and followed by the unloading of transshipment
cargoes.
If the unloading is over, then loading of export cargoes is to be
done, and followed by the loading of transshipment cargoes.
Input and Output Variables for Simulation
Items
Vessel
Input
Berth & Time
Quay Crane
Quay
Capability
Output
Berth
Vessel
Size
Input
Period
Inbound &
Outbound
Yard
Output
Occupancy
Variables
Time Interval on Ship Arriving
Amount
Number of Berth
Working Time
Number of allocated crane
Capability per hour
Quay Capability
Berth occupancy rate
Description
Distribution on Time Interval
Distribution on LPC
Berths by the port type
Working days and hours
For each LPC
Crane productivity
Annual throughput
Berth Occupying Time/Total Operating
Time
Ship waiting ratio
Berth waiting Time/Total Service Time
Time of staying in the port
Duration time from arriving to leaving
TGS
TGS by the type of cargo
Average stacking height
By the type of cargo
Dwell Time
By the type of cargo
In/Outbound status by the type By the type of cargo
of cargo
Working Time
By the type of cargo
Occupancy against total equipment
capacity
Yard Density
By the type of cargo
LOGIC OF ALGORITHM FOR SIMULATION MODEL
Second come
Berths are not available! Wait in queue!
First class prioritiy
Higher
Compare priorities
Berth 4 available!!!
Berths are not available! Wait in queue!
First come
Second class prioritiy
Cranes are available!!!
Service completed
Service
completed
There is
no crane
available!
Service completed
Wait for crane!
Berth 1
Berth 2
Berth 3
Berth 4
Quay Simulation Results
 Simulation Input Values by Port Type
No. of container
handling
(based on total work
hour)
No.
of
berth
No. of
crane
per
berth
Type
Ship’s arrival time
Distribution
JCT
-0.001 +
35*BETA
(0.931, 4.75)
20 + WEI (797,
1.58)
LOGN
(1.07, 0.435)
5
3
-0.001 + 55 *
BETA(0.937, 7.67)
• -0.001 + 499 * BETA(2.16, 1.32)
• 500 + 498 * BETA(0.991, 1.18)
• 1e+003 + 496 * BETA(0.896, 1.33)
• 1.5e+003 + 1.59e+003 * BETA(0.946, 2.69)
TRIA(1.8,2.6,3.4)
4
3
SCT
LPC
 Container terminal performance (berth)
Current performance
Recommended
Proper capacity
Current performance
Type
Average
berth
occupancy
(%)
Throughput
per berth
(TEU)
Optimal
berth
occupancy
(%)
Optimal
throughput
(TEU)
No. of
crane
per
ship
Average
service
time
(hr.)
Ship’ s
Stay
time
(hr.)
Container
Handled per
hour per ship
(TEU)
No. of
berthing
ship
JCT
50
430,000
62
630,000
3.09
15.1
16.6
84
1,441
SCT
59
510,000
60
520,000
2.94
13.9
15.9
100
1,475
Proper throughput calculation table (container yard)
Quay
Type
JCT
SCT
CY
Occupancy
ratio (%)
Throughput
57
490,000
62
530,000
67
580,000
55
480,000
60
520,000
65
567,000
Occupancy(%)
60
60
No of
berth
Length
TGS
470,000
Total:
5
berth
1,447m
10,484
400,000
Total:
4
berths
1,200m
10,950
Throughput
 Legend: O - Occupancy ratio (%); T - Throughput (TEU); Nb - No. of berths; L – Length in m;
TGS - Total ground slots
Economic Implication of Proper Throughput:
Cost strategy analysis
The proper service level should be decided by considering the combined
costs of both the operating costs of port system and ship’s waiting costs. This
leads to a proper throughput calculation.
Cost
Total Cost
Minimum
Cost
Service Cost
Waiting Cost
Optimal
Service
Level of Service
Service cost*
 Service cost items: wages, construction cost of various facilities,
additional cost for yard equipment purchase, maintenance cost,
depreciation, insurance (other service-related costs)
 Facilities: the length and number of berth, CY area and TGS, the
number of gate access lane, and level of facility.
 Equipment: the number and capacity of Q/C, the number and
capacity of T/C, the number and capacity of Y/T, the degree of
equipment automation.
 Manpower: the number and skill of employees, operator’s ability to
make use of resources (management and control capability)
* However, cost accounting needs careful calculation, i.e. the idle time in providing services should be considered in the cost
analysis. (If the level of service increases, the idle time of both service providers and service facilities is likely to increase.)
Waiting Cost
 It is not easy to exactly calculate how much cost the queuing system
causes.
 Waiting cost items: ship’s waiting cost, cargo backlog cost, and
hinterland traffic congestion cost.
 Costs at the wharf: THC (terminal handling charge), wharfage,
dockage, D/O fee, container cleaning fee, tariff, value-added tax,
customs clearance charge, carriage, stevedoring fee, forklift fee,
ODCY expenses (rehandling fee, shuttling charge)
 Congestion cost: charge for cargo handling beyond capacity, cost for
extended service hours.
Quantitative Model
 The problem of decision-making (minimization) based on a queuing system
hangs on how to balance between the waiting cost and the service level. It
can be calculated on the basis of the following formula:
Minimise: TC (S) = (I x C1) + (W x C2)
where,
TC (S) = total system cost based on the service level (S)
I = service provider’s total hours during a specific period
C1 = cost per unit hour in the hours
W = total waiting hours during a specific period
C2 = cost per unit hour in the waiting hours
Case Study: SCT terminal
 If a container terminal throughput > its proper throughput capacity -> increase
ship waiting/backlog-related costs and the social costs
 additional construction of ODCY (off dock container yard)
 traffic congestion of hinterland roads
 increasing contamination
 wages increases stemming from additional deployment of workforce
 increasing depreciation of various facilities and equipment
 risk taking coming from overtime or night work
 Nevertheless, many container terminals sometimes try to pursue growthoriented management in order to improve their productivity, thus causing the
problem of lowered service and quality.
 In case of 400,000 TEU
(Waiting ratio: 0.09, LPC ratio: 0.165, product cost: US$17.81)
TEU
Capital
Cost +
Fuel ($)
No of
Ship per
Day
Weight
Waiting
Ratio
Days
No of
Cntrs
Total
Product
Cost ($)
Cargo
Congestion
Cost ($)
Ship
Congestion
Cost ($)
1,000
20,482
4.0
0.13
0.09
365
2,819
50,198
857,483
349,873
2,700
28,487
4.0
0.23
0.09
365
13,464
239,792
7,246,996
860,945
4,024
35,614
4.0
0.21
0.09
365
18,321
326,303
9,003,993
982,745
5,300
46,851
4.0
0.17
0.09
365
19,535
347,911
7,771,633
1,046,557
6,400
55,637
4.0
0.17
0.09
365
23,589
420,119
9,384,614
1,242,810
8,400
71,263
4.0
0.08
0.09
365
14,570
259,485
2,727,708
749,119
9,000
70,856
4.0
0.0029390
0.09
365
573
10,214
3,944
27,363
10,000
73,446
4.0
0.0007348
0.09
365
159
2,837
274
7,091
93,030
1,656,859
36,996,645
5,266,504
Sum
 In case of 450,000 TEU
(Waiting ratio: 0.18, LPC ratio: 0.165, product cost: US$17.81)
TEU
Capital
Cost +
Fuel ($)
1,000
20,482
4.0
0.13
0.18
365
5,637
2,700
28,487
4.0
0.23
0.18
365
4,024
35,614
4.0
0.21
0.18
5,300
46,851
4.0
0.17
6,400
55,637
4.0
8,400
71,263
9,000
10,000
Sum
No of
Ship per
Day
Cargo
Congestion
Cost ($)
Ship
Congestion
Cost ($)
100,396
3,429,930
699,746
26,928
479,584
28,987,985
1,721,890
365
36,643
652,605
36,015,973
1,965,491
0.18
365
39,069
695,822
31,086,534
2,093,114
0.17
0.18
365
47,178
840,238
37,538,456
2,485,620
4.0
0.08
0.18
365
29,139
518,970
10,910,831
1,498,239
70,856
4.0
0.0029390
0.18
365
1,147
20,428
15,778
54,727
73,446
4.0
0.0007348
0.18
365
319
5,675
1,096
14,183
186,059
3,313,717
147,986,582
10,533,008
Weight
Waiting
Ratio
Days
No of
Cntrs
Total
Product
Cost ($)
 In case of 700,000 TEU
(Waiting ratio: 1.8, LPC ratio: 0.165, product cost: US$17.81)
TEU
Capital
Cost +
Fuel ($)
1,000
20,482
4.0
0.13
1.80
365
56,371
1,003,960
342,993,026
6,997,457
2,700
28,487
4.0
0.23
1.80
365
269,278
4,795,842
2,898,798,458
17,218,898
4,024
35,614
4.0
0.21
1.80
365
366,426
6,526,051
3,601,597,258
19,654,909
5,300
46,851
4.0
0.17
1.80
365
390,692
6,958,218
3,108,653,363
20,931,141
6,400
55,637
4.0
0.17
1.80
365
471,779
8,402,376
3,753,845,570
24,856,196
8,400
71,263
4.0
0.08
1.80
365
291,393
5,189,703
1,091,083,142
14,982,388
9,000
70,856
4.0
0.0029390
1.80
365
11,470
204,275
1,577,758
547,267
10,000
73,446
4.0
0.0007348
1.80
365
3,186
56,747
109,581
141,827
1,860,594
33,137,172
14,798,658,156
105,330,082
Sum
No of
Ship per
Day
Weight
Waiting
Ratio
Days
No of
Cntrs
Total
Product
Cost ($)
Cargo
Congestion
Cost ($)
Ship
Congestion
Cost ($)
 Ship and cargo congestion costs of ‘S’ terminal
Cargoes
Handled
(TEU)
Turnover
per berth
Ship
congestion
cost
Cargo
congestion
cost
350,000
22,020,250
88,081,000
3,676,050
84,236,000
2,925,836
11,418,718
14,344,553
102,256,603
400,000
25,166,000
100,664,000
4,201,200
84,236,000
5,266,504
36,996,645
42,263,150
130,700,350
450,000
28,311,750
113,247,000
4,726,350
84,236,000
10,533,008
147,986,582
158,519,590
247,481,940
500,000
31,457,500
125,830,000
5,251,500
84,236,000
15,799,512
332,969,809
348,769,321
438,256,821
550,000
34,603,250
138,413,000
5,776,650
84,236,000
20,480,849
559,517,168
579,998,017
670,010,667
600,000
37,749,000
150,996,000
6,301,800
84,236,000
33,939,693
1,536,502,655
1,570,442,349
1,660,980,149
650,000
40,894,750
163,579,000
6,826,950
84,236,000
51,494,707
3,537,061,999
3,588,556,706
3,679,619,656
700,000
44,040,500
176,162,000
7,352,100
84,236,000
105,330,082
14,798,658,156
14,903,988,238
14,995,576,338
Total
turnover
Variable
cost
Fixed
cost
Total
congestion
cost
Total cost
Relationship between turnover and ship waiting/backlog-related costs
4,000,000,000
total turnover
fixed cost
total congestion cost
Total Cost
C ost
3,000,000,000
2,000,000,000
y = 4E+07x 2 . 1 7 9 6
R 2 = 0.7954
1,000,000,000
0
350,000
400,000
450,000
500,000
550,000
600,000
C a rgoes Ha ndl ed ( T E U)
650,000
700,000
 Corporate profit and social costs of ‘S’ terminal
TEU
Total
turnover
Total
congestion
cost
Total cost
Social gain
Terminal
gain
Shippers'
cost
Shippers'
cost + Cargo
congestion
cost
350,000
88,081,000
14,344,553
102,256,603
-14,175,603
168,950
88,081,000
99,499,718
400,000
100,664,000
42,263,150
130,700,350
-30,036,350
12,226,800
100,664,000
137,660,645
450,000
113,247,000
158,519,590
247,481,940
-134,234,940
24,284,650
113,247,000
261,233,582
500,000
125,830,000
348,769,321
438,256,821
-312,426,821
36,342,500
125,830,000
458,799,809
550,000
138,413,000
579,998,017
670,010,667
-531,597,667
48,400,350
138,413,000
697,930,168
600,000
150,996,000
1,570,442,349
1,660,980,149
-1,509,984,149
60,458,200
150,996,000
1,687,498,655
650,000
163,579,000
3,588,556,706
3,679,619,656
-3,516,040,656
72,516,050
163,579,000
3,700,640,999
700,000
176,162,000
14,903,988,238
14,995,576,338
-14,819,414,338
84,573,900
176,162,000
14,974,820,156
Relationship between corporate profit and social costs of ‘S’ terminal
6,000,000,000
Social Gain
Terminal Gain
4,000,000,000
Shippers ' Cos t
Shippers ' Cos t + Cargo
Conges tion Cos t
C ost
2,000,000,000
0
350,000
400,000
450,000
500,000
550,000
-2,000,000,000
-4,000,000,000
-6,000,000,000
C a rgoes Ha ndl ed ( T E U)
600,000
650,000
700,000
CONCLUSION
The obtained results have revealed that simulation modeling is a very
effective method to examine the proper throughput of container terminal
including berth side and yard side.
The proper throughput is to be identified in terms of both operational and
economic view
 In a result, it is necessary to recognize the the capability of infrastructure
is dependent on many factors like operation systems, policy, equipment and
infrastructure.
 On the context, the regular check will be needed for improving service
and reducing cost, as proper throughput varies on situation.
THANK YOU
for Listening