CONTAINER Terminals Modeling
Nam-Kyu ParkProfessor
Tongmyong University, Department of Logistics
Management
Branislav DragovićAssociate 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 ship-berth
linkage design and modeling
Considered problems
Approaches References
Simulation of container terminals (CT) and ports
Modsim IIIObject oriented programming, C++ARENAARENA, SLXVisual SLAMAweSimWitness softwareTaylor IIGPSS/H
Extend-version 3.2.2Scenario generator
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;
Overview concept
Quantitative models for variousdecision problems in CTLogistics processes and operations in CT – optimization methods
Vis and Koster, 2003;
Steenken, et al., 2004.
Table 1: Literature review of a container port and ship-berth link planning by using simulation
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.
C/C assignment by berth
Ship arrival
LPC by ship
Berth allocation
Loading and unloading CY allocation
Ship departure
Flow of quay simulation model
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.
Items Variables Description
Quay
Input
VesselTime Interval on Ship Arriving Distribution on Time IntervalAmount Distribution on LPC
Berth & TimeNumber of Berth Berths by the port typeWorking Time Working days and hours
Quay CraneNumber of allocated crane For each LPCCapability per hour Crane productivity
Output
Capability Quay Capability Annual throughput
BerthBerth occupancy rate Berth Occupying Time/Total Operating
Time
VesselShip waiting ratio Berth waiting Time/Total Service TimeTime of staying in the port Duration time from arriving to leaving
Yard
Input
SizeTGS TGS by the type of cargoAverage stacking height By the type of cargo
Period Dwell Time By the type of cargo
Inbound & Outbound
In/Outbound status by the type of cargo
By the type of cargo
Working Time By the type of cargo
Output Occupancy Yard DensityOccupancy against total equipment capacityBy the type of cargo
Input and Output Variables for Simulation
Berths are not available! Wait in queue!
Berths are not available! Wait in queue!
First comeSecond class prioritiy
Second come
First class prioritiy
Service completed
Compare prioritiesHigher
Service completedThere is no crane available! Wait for crane!
Service completed
Cranes are available!!!
Berth 4 available!!!
Berth 1 Berth 2 Berth 3 Berth 4
LOGIC OF ALGORITHM FOR SIMULATION MODEL
Quay Simulation Results
TypeShip’s arrival time
DistributionLPC
No. of containerhandling
(based on total work hour)
No. of
berth
No. of crane per
berth
JCT -0.001 +
35*BETA
(0.931, 4.75)
20 + WEI (797,
1.58)
LOGN
(1.07, 0.435)5 3
SCT -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
Simulation Input Values by Port Type
Type
Current performanceRecommended Proper capacity
Current performance
Average berth
occupancy(%)
Throughput per berth
(TEU)
Optimal berth
occupancy(%)
Optimal throughput
(TEU)
No. ofcrane
per ship
Averageservice
time(hr.)
Ship’ sStay time(hr.)
ContainerHandled perhour 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
Container terminal performance (berth)
Type
Quay CYNo ofberth
Length TGSOccupancy ratio (%)
ThroughputOccu-
pancy(%)Throughput
JCT
57 490,000
60 470,000Total:
5berth
1,447m 10,48462 530,000
67 580,000
SCT
55 480,000
60 400,000Total:
4 berths
1,200m 10,95060 520,000
65 567,000
Legend: O - Occupancy ratio (%); T - Throughput (TEU); Nb - No. of berths; L – Length in m;
TGS - Total ground slots
Proper throughput calculation table (container yard)
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.
Total CostCost
Service Cost
Waiting Cost
Level of ServiceOptimalService
MinimumCost
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.
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 periodC1 = cost per unit hour in the hoursW = total waiting hours during a specific periodC2 = cost per unit hour in the waiting hours
Quantitative Model
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 growth-oriented management in order to improve their productivity, thus causing the problem of lowered service and quality.
Case Study: SCT terminal
In case of 400,000 TEU
(Waiting ratio: 0.09, LPC ratio: 0.165, product cost: US$17.81)
TEUCapital Cost + Fuel ($)
No of Ship per
DayWeight
Waiting Ratio
DaysNo 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
Sum 93,030 1,656,859 36,996,645 5,266,504
In case of 450,000 TEU
(Waiting ratio: 0.18, LPC ratio: 0.165, product cost: US$17.81)
TEUCapital Cost + Fuel ($)
No of Ship per
DayWeight
Waiting Ratio
DaysNo of Cntrs
Total Product Cost ($)
Cargo Congestion
Cost ($)
Ship Congestion
Cost ($)
1,000 20,482 4.0 0.13 0.18 365 5,637 100,396 3,429,930 699,746
2,700 28,487 4.0 0.23 0.18 365 26,928 479,584 28,987,985 1,721,890
4,024 35,614 4.0 0.21 0.18 365 36,643 652,605 36,015,973 1,965,491
5,300 46,851 4.0 0.17 0.18 365 39,069 695,822 31,086,534 2,093,114
6,400 55,637 4.0 0.17 0.18 365 47,178 840,238 37,538,456 2,485,620
8,400 71,263 4.0 0.08 0.18 365 29,139 518,970 10,910,831 1,498,239
9,000 70,856 4.0 0.0029390 0.18 365 1,147 20,428 15,778 54,727
10,000 73,446 4.0 0.0007348 0.18 365 319 5,675 1,096 14,183
Sum 186,059 3,313,717 147,986,582 10,533,008
In case of 700,000 TEU
(Waiting ratio: 1.8, LPC ratio: 0.165, product cost: US$17.81)
TEUCapital Cost + Fuel ($)
No of Ship per
DayWeight
Waiting Ratio
DaysNo of Cntrs
Total Product Cost ($)
Cargo Congestion
Cost ($)
Ship Congestion
Cost ($)
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
Sum 1,860,594 33,137,172 14,798,658,156 105,330,082
Cargoes Handled
(TEU)
Turnover per berth
Total turnover
Variable cost
Fixed cost
Ship congestion
cost
Cargo congestion
cost
Total congestion
costTotal 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
Ship and cargo congestion costs of ‘S’ terminal
y = 4E+07x2. 1796
R2 = 0.7954
0
1,000,000,000
2,000,000,000
3,000,000,000
4,000,000,000
350,000 400,000 450,000 500,000 550,000 600,000 650,000 700,000
Cargoes Handled (TEU)
Cost
total turnoverfixed costtotal congestion costTotal Cost
Relationship between turnover and ship waiting/backlog-related costs
TEUTotal
turnover
Total congestion
costTotal 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
Corporate profit and social costs of ‘S’ terminal
- 6,000,000,000
- 4,000,000,000
- 2,000,000,000
0
2,000,000,000
4,000,000,000
6,000,000,000
350,000 400,000 450,000 500,000 550,000 600,000 650,000 700,000
Cargoes Handled (TEU)
Cost
Social Gain
Terminal Gain
Shippers ' Cost
Shippers ' Cost + CargoCongestion Cost
Relationship between corporate profit and social costs of ‘S’ terminal
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.
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