Project Presentation For ECIV 705 - Deterministic Civil and Environmental Systems Engineering
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Transcript of Project Presentation For ECIV 705 - Deterministic Civil and Environmental Systems Engineering
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P r o j e c t P r e s e n t a t i o n
ForECIV 705 - Deterministic Civil and Environmental Systems Engineering
Implementation and Performance Evaluation of a Proposed Integer
Model for Yard Crane Scheduling Problem
Omor Sharif
S p r i n g 2 0 1 0
U n i v e r s i t y o f S o u t h C a r o l i n a , C o l u m b i a
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To p i c s
1. Introduction- Problem Description and Motivation
2. Formulation – Integer Program
3. Solution and Performance Evaluation
4. Results and Conclusion
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Pr o b l e m D e s c r i p t i o n a n d M o t i v a t i o n
Courtesy: (Ng- 2005)
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Problem Description and Motivation
-To determine the job handling (truck serving) sequence of
cranes
-Want to minimize waiting time for trucks
-Trucks with different arrival time
-Jobs are distributed in space
-Idling trucks are source of potential emission impacts on the
ambient environment
-Productivity of yards cranes is crucial for terminals
operational efficiency
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Project Objectives
-To Implement an integer programming model developed by W. C. Ng (2005)
-To find optimal and effective allocation of the yard cranes to handle jobs with different ready times
-Performance Evaluation of the proposed integer model
Courtesy: (Ng- 2005)
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I n te g e r P ro g ra m
Definition of Parameters
Number of jobs to be handled in a planning period, n
Number of cranes available, m
Number of slots,
Time required to handle a job, h = 8 time units
Time required to travel one slot by a crane = 1 time unit
Ready time (truck arrival time) of job i is ri
Location of Job i in terms of slot number is βi
Set of slots the yard crane can possibly be in at period t-1 is p(l)
Set of slots the yard crane can possibly be in at period t+1 is s(l)
Location of yard crane k at period 0 (initial location in terms of slot number) is αk
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I n te g e r P ro g ra m
The objective function used is to minimize the sum of total job
completion time. Formally,
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C o n s t ra i n t s
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N o tes o n C o n s t ra i n t s
Constraints (1) give the relationship between a job's completion time, ready time and handling time. Constraints (2) ensure that there is only one non-zero completion time for each job given by W.Constraints (3) ensure that during a yard crane job handling operation, the yard crane stays at the job location throughout the operation. Constraints (4) and (5) state the relationship between the locations visited by a yard crane, as implied by Y, in successive periods. Constraints (6) ensure that the movement defined by Y is free of inter-crane inter ference. Constraints (7) state that a yard crane can only be in one of the slots in the yard zone in each period. Constraints (8) give the relationship between the completion time of a job and that of its successors. Constraints (9) give the relationship between X and W for jobs handled by the same yard crane. Con straints (10) are simple binary constraints.
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An Examplethe || marks indicates cranes position at t = 0
|| ||
Row 1 1(1) 3 (6)
Row 2 2 (4) 7 (16)
Row 3 4 (9) 6 (14)
Row 4 5 (11)
Slot 1 Slot 2 Slot 3 Slot 4 Slot 5
Optimal Schedule
Value of Objective Function =149 time unitsCrane 1 handles job {1,4,5,6}Crane 2 handles job {2,3,7}
Courtesy: (Ng- 2005)
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S o m e Re s u l t s
Number of Slots, Number of Jobs,
n
Value of Objective
Function (Time units)
Solution time
(hr:min:sec)*
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5 68 (with h = 4) 00:00:40
10 180 (with h = 4) 00:18:00
15 240 (with h = 2) 01:36:06
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5 75 (with h = 4) 00:00:52
10 189 (with h = 4) 00:08:36
15 260 (with h = 2) 08:01:06
155 90 (with h = 4) 00:01:00
10 232 (with h = 4) 02:11:32
205 94 (with h = 4) 00:01:11
10 241 (with h = 4) 06:22:19
* Solution time applies to test cases instance only
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C o n c l u s i o n
1. The integer program finds the optimal schedule for small scale
problem sizes
2. Solution time increases much rapidly even if the size of the
problem is increased gradually.
3. For large and realistic sized problems the time required to solve
the model will most often exceed the time bound within which a
solution is desirable.
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Re fere n c e s
1. Ng, W.C., Crane scheduling in container yards with inter-crane interference.
European Journal of Operational Research, 2005. 164(1): p. 64-78.
2. Ng, W.C. and K.L. Mak, Yard crane scheduling in port container terminals. Applied
Mathematical Modelling, 2005. 29(3): p. 263-276.
3. Zhang, C., et al., Dynamic crane deployment in container storage yards.
Transportation Research Part B: Methodological, 2002. 36(6): p. 537-555.
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