SlideShare a Scribd company logo
1 of 4
AssignmentNo.1
Findthe Shortesttourfrom the followinggraphusingACO-TSP(antColonyOptimization-Travelling
SalesmanProblem) wherethe graphrepresentsasetof nodesanddistance betweeneverypairof
nodes.The shortestpossibleroute mustvisit everynode exactlyonce andreturntothe startingpoint.
(Assume startnode is1)
Solution:
Steps:
1. Considernode1asthe startingand endingpoint.
2. Generate all (n-1)!Permutationsof nodes.
3. Calculate costof everypermutationandkeeptrackof minimum costpermutation.
4. Returnthe permutationwithminimumcost.
Sl No. Permutations Corresponding cost
1 1-2-3-4-1 95(10+35+30+20)
2 1-2-4-3-1 80(10+25+30+15)
3 1-3-2-4-1 95(15+35+25+20)
4 1-3-4-2-1 80(15+30+25+10)
5 1-4-3-2-1 95(20+30+35+10)
6 1-4-2-3-1 95(20+25+35+15)
Weightage Matrix:
1 2 3 4
1 0 10 15 20
2 10 0 35 25
3 15 35 0 30
4 20 25 30 0
Let usassume,start node 1, considerasS
Iteration
No.
Cost function Evaluation Cost Path
1 C(4,S) D(4,1) 20 1-4
C(3,S) D(3,1) 15 1-3
C(2,S) D(2,1) 10 1-2
2 C(2,{3}) D(2,3)+C(3,S) 35+15=50 1-3-2
C(2, {4}) D(2,4)+C(4,S) 25+20=45 1-4-2
C(3,{2}) D(3,2)+C(2,S) 35+10=45 1-2-3
C(3,{4}) D(3,4)+C(4,S) 30+20=50 1-4-3
C(4,{2}) D(4,2)+C(2,S) 25+10=35 1-2-4
C(4,{3}) D(4,3)+C(3,S) 30+15=45 1-3-4
3 C(2,{3,4}) MIN(D(2,3) + C(3,{4}),
D(2,4)+C(4,{3}))
MIN(50+35,45+25)
=80
1-3-4-2
C(3,{2,4}) MIN(D(3,2)+C(2,{4}),
D(3,4)+C(4,{2}))
MIN(45+35,35+30)
=65
1-2-4-3
C(4,{2,3}) MIN(D(4,2)+C(2,{3}),
D(4,3)+C(3,{2}))
MIN(50+25,45+30)
=75
1-2-3-4
4 C(1,{2,3,4}) MIN(D(1,2)+C(2,{3,4})
, D(1,3)+C(3,{2,4}),
D(1,4)+ C(4,{2,3}))
MIN(90,80,95)
=80
1-2-4-3-1
SO,THE OPTIMAL PATH 1-2-4-3-1 FOR TOUR HAS LENGTH 80.
AssignmentNo.2
There are 5 teams:T1, T2, T3, T4 and T5 ina couple of serieswhere 3typesof games:G1, G2
and G3. NowT1 and T3 bothplaysall three typesof games,T2 playsonlyG1 and G3, T4 plays
onlyG2 and G3 andT5 onlyplaysG1 and G3.
NowusingAntColonyOptimizationfindoutthe schedulingof gamesamongG1,G2 and G3.
Solution:
Here create a matrix Cij where ithrepresentsteamandjthrepresentsgame.Now consider1
for playinggame and0 for non-playinggame.
G1 G2 G3
T1 1 1 1
T2 1 0 1
T3 1 1 1
T4 0 1 1
T5 1 0 1
Now,the weightage Dij representsthe numberof competitorswherethe competitor
participatesinboththe gamesI and j.
Thisweightage functionformsamatrix whichisknownasweightage matrix.
D3x3
G1 G2 G3
G1 0 2 4
G2 2 0 3
G3 4 3 0
SL NO PERMUTATION PATH COST
1 1-2-3-1 9
2 1-3-2-1 9
3 2-1-3-2 9
4 2-3-1-2 9
5 3-1-2-3 9
1
2
3
2 4
3
6 3-2-1-3 9
Let us assume start node 1 (S)
IterationNo. Cost function Evaluation Cost Path
1 C(2,S) D(2,1) 2 1-2
C(3,S) D(3,1) 4 1-3
2 C(3,{2}) D(3,2)+C(2,S) 3+2=5 1-2-3
C(2,{3}) D(2,3)+C(3,S) 3+4=7 1-3-2
MIN(C(3,{2}),C(2,{3}))=MIN(5,7) =5 SO,PATH 1-2-3
Let us assume start node 2 (S)
IterationNo. Cost function Evaluation Cost Path
1 C(1,S) D(1,2) 2 2-1
C(3,S) D(3,2) 3 2-3
2 C(3,{1}) D(3,1)+C(1,S) 4+2=6 2-1-3
C(1,{3}) D(1,3)+C(3,S) 4+3=7 2-3-1
MIN(C(3,{1}),C(1,{3}))=MIN(6,7) =6 SO,PATH 2-1-3
Let us assume start node 3 (S)
IterationNo. Cost function Evaluation Cost Path
1 C(2,S) D(2,3) 3 3-2
C(1,S) D(1,3) 4 3-1
2 C(1,{2}) D(1,2)+C(2,S) 2+3=5 3-2-1
C(2,{1}) D(2,1)+C(1,S) 2+4=6 3-1-2
MIN(C(1,{2}),C(2,{1}))=MIN(5,6) =5 SO,PATH 3-2-1
So overall minimizationeitherpathschedule 1-2-3or 3-2-1
So,G1-G2-G3 OR G3-G2-G1.

More Related Content

What's hot

Dynamic programming - fundamentals review
Dynamic programming - fundamentals reviewDynamic programming - fundamentals review
Dynamic programming - fundamentals reviewElifTech
 
Knapsack problem using greedy approach
Knapsack problem using greedy approachKnapsack problem using greedy approach
Knapsack problem using greedy approachpadmeshagrekar
 
Heuristc Search Techniques
Heuristc Search TechniquesHeuristc Search Techniques
Heuristc Search TechniquesJismy .K.Jose
 
Branch and bounding : Data structures
Branch and bounding : Data structuresBranch and bounding : Data structures
Branch and bounding : Data structuresKàŕtheek Jåvvàjí
 
BackTracking Algorithm: Technique and Examples
BackTracking Algorithm: Technique and ExamplesBackTracking Algorithm: Technique and Examples
BackTracking Algorithm: Technique and ExamplesFahim Ferdous
 
Travelling salesman dynamic programming
Travelling salesman dynamic programmingTravelling salesman dynamic programming
Travelling salesman dynamic programmingmaharajdey
 
AI 7 | Constraint Satisfaction Problem
AI 7 | Constraint Satisfaction ProblemAI 7 | Constraint Satisfaction Problem
AI 7 | Constraint Satisfaction ProblemMohammad Imam Hossain
 
Assignment problem branch and bound.pptx
Assignment problem branch and bound.pptxAssignment problem branch and bound.pptx
Assignment problem branch and bound.pptxKrishnaVardhan50
 
Adversarial search with Game Playing
Adversarial search with Game PlayingAdversarial search with Game Playing
Adversarial search with Game PlayingAman Patel
 
AI - Local Search - Hill Climbing
AI - Local Search - Hill ClimbingAI - Local Search - Hill Climbing
AI - Local Search - Hill ClimbingAndrew Ferlitsch
 
Traveling salesman problem
Traveling salesman problemTraveling salesman problem
Traveling salesman problemJayesh Chauhan
 
Job sequencing with deadline
Job sequencing with deadlineJob sequencing with deadline
Job sequencing with deadlineArafat Hossan
 
0 1 knapsack using branch and bound
0 1 knapsack using branch and bound0 1 knapsack using branch and bound
0 1 knapsack using branch and boundAbhishek Singh
 
Travelling SalesMan Problem(TSP)
Travelling SalesMan Problem(TSP)Travelling SalesMan Problem(TSP)
Travelling SalesMan Problem(TSP)Akshay Kamble
 
Travelling salesman problem
Travelling salesman problemTravelling salesman problem
Travelling salesman problemWajahat Hussain
 

What's hot (20)

5 csp
5 csp5 csp
5 csp
 
Dynamic programming - fundamentals review
Dynamic programming - fundamentals reviewDynamic programming - fundamentals review
Dynamic programming - fundamentals review
 
Knapsack problem using greedy approach
Knapsack problem using greedy approachKnapsack problem using greedy approach
Knapsack problem using greedy approach
 
Heuristc Search Techniques
Heuristc Search TechniquesHeuristc Search Techniques
Heuristc Search Techniques
 
Branch and bounding : Data structures
Branch and bounding : Data structuresBranch and bounding : Data structures
Branch and bounding : Data structures
 
BackTracking Algorithm: Technique and Examples
BackTracking Algorithm: Technique and ExamplesBackTracking Algorithm: Technique and Examples
BackTracking Algorithm: Technique and Examples
 
Maximum flow
Maximum flowMaximum flow
Maximum flow
 
Travelling salesman dynamic programming
Travelling salesman dynamic programmingTravelling salesman dynamic programming
Travelling salesman dynamic programming
 
AI 7 | Constraint Satisfaction Problem
AI 7 | Constraint Satisfaction ProblemAI 7 | Constraint Satisfaction Problem
AI 7 | Constraint Satisfaction Problem
 
Randomized algorithms ver 1.0
Randomized algorithms ver 1.0Randomized algorithms ver 1.0
Randomized algorithms ver 1.0
 
Assignment problem branch and bound.pptx
Assignment problem branch and bound.pptxAssignment problem branch and bound.pptx
Assignment problem branch and bound.pptx
 
Adversarial search with Game Playing
Adversarial search with Game PlayingAdversarial search with Game Playing
Adversarial search with Game Playing
 
AI - Local Search - Hill Climbing
AI - Local Search - Hill ClimbingAI - Local Search - Hill Climbing
AI - Local Search - Hill Climbing
 
Greedy Algorihm
Greedy AlgorihmGreedy Algorihm
Greedy Algorihm
 
Traveling salesman problem
Traveling salesman problemTraveling salesman problem
Traveling salesman problem
 
Job sequencing with deadline
Job sequencing with deadlineJob sequencing with deadline
Job sequencing with deadline
 
0 1 knapsack using branch and bound
0 1 knapsack using branch and bound0 1 knapsack using branch and bound
0 1 knapsack using branch and bound
 
Travelling SalesMan Problem(TSP)
Travelling SalesMan Problem(TSP)Travelling SalesMan Problem(TSP)
Travelling SalesMan Problem(TSP)
 
Travelling salesman problem
Travelling salesman problemTravelling salesman problem
Travelling salesman problem
 
Graph coloring problem
Graph coloring problemGraph coloring problem
Graph coloring problem
 

Similar to Traveling salesman problem: Game Scheduling Problem Solution: Ant Colony Optimization

Analysis of Electro-Mechanical System
Analysis of Electro-Mechanical SystemAnalysis of Electro-Mechanical System
Analysis of Electro-Mechanical SystemCOMSATS Abbottabad
 
The Delta Of An Arithmetic Asian Option Via The Pathwise Method
The Delta Of An Arithmetic Asian Option Via The Pathwise MethodThe Delta Of An Arithmetic Asian Option Via The Pathwise Method
The Delta Of An Arithmetic Asian Option Via The Pathwise MethodAnna Borisova
 
Hull White model presentation
Hull White model presentationHull White model presentation
Hull White model presentationStephan Chang
 
DSP LAB COMPLETE CODES.docx
DSP LAB COMPLETE CODES.docxDSP LAB COMPLETE CODES.docx
DSP LAB COMPLETE CODES.docxMUMAR57
 
Quantum espresso G Vector distributon
Quantum espresso G Vector distributonQuantum espresso G Vector distributon
Quantum espresso G Vector distributonEric Pascolo
 
Filter design and simulation
Filter design and simulationFilter design and simulation
Filter design and simulationSandesh Agrawal
 
Asymptotic Notation and Complexity
Asymptotic Notation and ComplexityAsymptotic Notation and Complexity
Asymptotic Notation and ComplexityRajandeep Gill
 
BALLANDBEAM_GROUP7.pptx
BALLANDBEAM_GROUP7.pptxBALLANDBEAM_GROUP7.pptx
BALLANDBEAM_GROUP7.pptxOthmanBensaoud
 
Introduction to Algorithms
Introduction to AlgorithmsIntroduction to Algorithms
Introduction to Algorithmspppepito86
 
CS8451 - Design and Analysis of Algorithms
CS8451 - Design and Analysis of AlgorithmsCS8451 - Design and Analysis of Algorithms
CS8451 - Design and Analysis of AlgorithmsKrishnan MuthuManickam
 
Order-Picking-Policies.ppt
Order-Picking-Policies.pptOrder-Picking-Policies.ppt
Order-Picking-Policies.pptTaspiyaAfroz
 
Idea for ineractive programming language
Idea for ineractive programming languageIdea for ineractive programming language
Idea for ineractive programming languageLincoln Hannah
 

Similar to Traveling salesman problem: Game Scheduling Problem Solution: Ant Colony Optimization (20)

Analysis of Electro-Mechanical System
Analysis of Electro-Mechanical SystemAnalysis of Electro-Mechanical System
Analysis of Electro-Mechanical System
 
algorithm Unit 3
algorithm Unit 3algorithm Unit 3
algorithm Unit 3
 
The Delta Of An Arithmetic Asian Option Via The Pathwise Method
The Delta Of An Arithmetic Asian Option Via The Pathwise MethodThe Delta Of An Arithmetic Asian Option Via The Pathwise Method
The Delta Of An Arithmetic Asian Option Via The Pathwise Method
 
2_1 Edit Distance.pptx
2_1 Edit Distance.pptx2_1 Edit Distance.pptx
2_1 Edit Distance.pptx
 
Hull White model presentation
Hull White model presentationHull White model presentation
Hull White model presentation
 
DSP LAB COMPLETE CODES.docx
DSP LAB COMPLETE CODES.docxDSP LAB COMPLETE CODES.docx
DSP LAB COMPLETE CODES.docx
 
Hprec7.1
Hprec7.1Hprec7.1
Hprec7.1
 
Unit 3 daa
Unit 3 daaUnit 3 daa
Unit 3 daa
 
Quantum espresso G Vector distributon
Quantum espresso G Vector distributonQuantum espresso G Vector distributon
Quantum espresso G Vector distributon
 
Filter design and simulation
Filter design and simulationFilter design and simulation
Filter design and simulation
 
Computer graphics 2
Computer graphics 2Computer graphics 2
Computer graphics 2
 
Xgboost
XgboostXgboost
Xgboost
 
Asymptotic Notation and Complexity
Asymptotic Notation and ComplexityAsymptotic Notation and Complexity
Asymptotic Notation and Complexity
 
Asymptotic Notation
Asymptotic NotationAsymptotic Notation
Asymptotic Notation
 
Time complexity.ppt
Time complexity.pptTime complexity.ppt
Time complexity.ppt
 
BALLANDBEAM_GROUP7.pptx
BALLANDBEAM_GROUP7.pptxBALLANDBEAM_GROUP7.pptx
BALLANDBEAM_GROUP7.pptx
 
Introduction to Algorithms
Introduction to AlgorithmsIntroduction to Algorithms
Introduction to Algorithms
 
CS8451 - Design and Analysis of Algorithms
CS8451 - Design and Analysis of AlgorithmsCS8451 - Design and Analysis of Algorithms
CS8451 - Design and Analysis of Algorithms
 
Order-Picking-Policies.ppt
Order-Picking-Policies.pptOrder-Picking-Policies.ppt
Order-Picking-Policies.ppt
 
Idea for ineractive programming language
Idea for ineractive programming languageIdea for ineractive programming language
Idea for ineractive programming language
 

More from Soumen Santra

Cell hole identification in carcinogenic segment using Geodesic Methodology: ...
Cell hole identification in carcinogenic segment using Geodesic Methodology: ...Cell hole identification in carcinogenic segment using Geodesic Methodology: ...
Cell hole identification in carcinogenic segment using Geodesic Methodology: ...Soumen Santra
 
PPT_PAPERID 31_SOUMEN_SANTRA - ICCET23.pptx
PPT_PAPERID 31_SOUMEN_SANTRA - ICCET23.pptxPPT_PAPERID 31_SOUMEN_SANTRA - ICCET23.pptx
PPT_PAPERID 31_SOUMEN_SANTRA - ICCET23.pptxSoumen Santra
 
Basic networking hardware: Switch : Router : Hub : Bridge : Gateway : Bus : C...
Basic networking hardware: Switch : Router : Hub : Bridge : Gateway : Bus : C...Basic networking hardware: Switch : Router : Hub : Bridge : Gateway : Bus : C...
Basic networking hardware: Switch : Router : Hub : Bridge : Gateway : Bus : C...Soumen Santra
 
Optimization techniques: Ant Colony Optimization: Bee Colony Optimization: Tr...
Optimization techniques: Ant Colony Optimization: Bee Colony Optimization: Tr...Optimization techniques: Ant Colony Optimization: Bee Colony Optimization: Tr...
Optimization techniques: Ant Colony Optimization: Bee Colony Optimization: Tr...Soumen Santra
 
A Novel Real Time Home Automation System with Google Assistance Technology
A Novel Real Time Home Automation System with Google Assistance TechnologyA Novel Real Time Home Automation System with Google Assistance Technology
A Novel Real Time Home Automation System with Google Assistance TechnologySoumen Santra
 
Java basic part 2 : Datatypes Keywords Features Components Security Exceptions
Java basic part 2 : Datatypes Keywords Features Components Security Exceptions Java basic part 2 : Datatypes Keywords Features Components Security Exceptions
Java basic part 2 : Datatypes Keywords Features Components Security Exceptions Soumen Santra
 
Threads Advance in System Administration with Linux
Threads Advance in System Administration with LinuxThreads Advance in System Administration with Linux
Threads Advance in System Administration with LinuxSoumen Santra
 
Frequency Division Multiplexing Access (FDMA)
Frequency Division Multiplexing Access (FDMA)Frequency Division Multiplexing Access (FDMA)
Frequency Division Multiplexing Access (FDMA)Soumen Santra
 
Carrier Sense Multiple Access With Collision Detection (CSMA/CD) Details : Me...
Carrier Sense Multiple Access With Collision Detection (CSMA/CD) Details : Me...Carrier Sense Multiple Access With Collision Detection (CSMA/CD) Details : Me...
Carrier Sense Multiple Access With Collision Detection (CSMA/CD) Details : Me...Soumen Santra
 
Code-Division Multiple Access (CDMA)
Code-Division Multiple Access (CDMA)Code-Division Multiple Access (CDMA)
Code-Division Multiple Access (CDMA)Soumen Santra
 
PURE ALOHA : MEDIUM ACCESS CONTROL PROTOCOL (MAC): Definition : Types : Details
PURE ALOHA : MEDIUM ACCESS CONTROL PROTOCOL (MAC): Definition : Types : DetailsPURE ALOHA : MEDIUM ACCESS CONTROL PROTOCOL (MAC): Definition : Types : Details
PURE ALOHA : MEDIUM ACCESS CONTROL PROTOCOL (MAC): Definition : Types : DetailsSoumen Santra
 
Carrier-sense multiple access with collision avoidance CSMA/CA
Carrier-sense multiple access with collision avoidance CSMA/CACarrier-sense multiple access with collision avoidance CSMA/CA
Carrier-sense multiple access with collision avoidance CSMA/CASoumen Santra
 
RFID (RADIO FREQUENCY IDENTIFICATION)
RFID (RADIO FREQUENCY IDENTIFICATION)RFID (RADIO FREQUENCY IDENTIFICATION)
RFID (RADIO FREQUENCY IDENTIFICATION)Soumen Santra
 
SPACE DIVISION MULTIPLE ACCESS (SDMA) SATELLITE COMMUNICATION
SPACE DIVISION MULTIPLE ACCESS (SDMA) SATELLITE COMMUNICATION  SPACE DIVISION MULTIPLE ACCESS (SDMA) SATELLITE COMMUNICATION
SPACE DIVISION MULTIPLE ACCESS (SDMA) SATELLITE COMMUNICATION Soumen Santra
 
Threads Basic : Features, Types & Implementation
Threads Basic : Features, Types  & ImplementationThreads Basic : Features, Types  & Implementation
Threads Basic : Features, Types & ImplementationSoumen Santra
 
CLOUD COMPUTING : BASIC CONCEPT REGARDING LOAD BALANCING AND Virtual Machine ...
CLOUD COMPUTING : BASIC CONCEPT REGARDING LOAD BALANCING AND Virtual Machine ...CLOUD COMPUTING : BASIC CONCEPT REGARDING LOAD BALANCING AND Virtual Machine ...
CLOUD COMPUTING : BASIC CONCEPT REGARDING LOAD BALANCING AND Virtual Machine ...Soumen Santra
 
JavaScript with Syntax & Implementation
JavaScript with Syntax & ImplementationJavaScript with Syntax & Implementation
JavaScript with Syntax & ImplementationSoumen Santra
 

More from Soumen Santra (20)

Cell hole identification in carcinogenic segment using Geodesic Methodology: ...
Cell hole identification in carcinogenic segment using Geodesic Methodology: ...Cell hole identification in carcinogenic segment using Geodesic Methodology: ...
Cell hole identification in carcinogenic segment using Geodesic Methodology: ...
 
PPT_PAPERID 31_SOUMEN_SANTRA - ICCET23.pptx
PPT_PAPERID 31_SOUMEN_SANTRA - ICCET23.pptxPPT_PAPERID 31_SOUMEN_SANTRA - ICCET23.pptx
PPT_PAPERID 31_SOUMEN_SANTRA - ICCET23.pptx
 
Basic networking hardware: Switch : Router : Hub : Bridge : Gateway : Bus : C...
Basic networking hardware: Switch : Router : Hub : Bridge : Gateway : Bus : C...Basic networking hardware: Switch : Router : Hub : Bridge : Gateway : Bus : C...
Basic networking hardware: Switch : Router : Hub : Bridge : Gateway : Bus : C...
 
Optimization techniques: Ant Colony Optimization: Bee Colony Optimization: Tr...
Optimization techniques: Ant Colony Optimization: Bee Colony Optimization: Tr...Optimization techniques: Ant Colony Optimization: Bee Colony Optimization: Tr...
Optimization techniques: Ant Colony Optimization: Bee Colony Optimization: Tr...
 
Quick Sort
Quick SortQuick Sort
Quick Sort
 
Merge sort
Merge sortMerge sort
Merge sort
 
A Novel Real Time Home Automation System with Google Assistance Technology
A Novel Real Time Home Automation System with Google Assistance TechnologyA Novel Real Time Home Automation System with Google Assistance Technology
A Novel Real Time Home Automation System with Google Assistance Technology
 
Java basic part 2 : Datatypes Keywords Features Components Security Exceptions
Java basic part 2 : Datatypes Keywords Features Components Security Exceptions Java basic part 2 : Datatypes Keywords Features Components Security Exceptions
Java basic part 2 : Datatypes Keywords Features Components Security Exceptions
 
Java Basic PART I
Java Basic PART IJava Basic PART I
Java Basic PART I
 
Threads Advance in System Administration with Linux
Threads Advance in System Administration with LinuxThreads Advance in System Administration with Linux
Threads Advance in System Administration with Linux
 
Frequency Division Multiplexing Access (FDMA)
Frequency Division Multiplexing Access (FDMA)Frequency Division Multiplexing Access (FDMA)
Frequency Division Multiplexing Access (FDMA)
 
Carrier Sense Multiple Access With Collision Detection (CSMA/CD) Details : Me...
Carrier Sense Multiple Access With Collision Detection (CSMA/CD) Details : Me...Carrier Sense Multiple Access With Collision Detection (CSMA/CD) Details : Me...
Carrier Sense Multiple Access With Collision Detection (CSMA/CD) Details : Me...
 
Code-Division Multiple Access (CDMA)
Code-Division Multiple Access (CDMA)Code-Division Multiple Access (CDMA)
Code-Division Multiple Access (CDMA)
 
PURE ALOHA : MEDIUM ACCESS CONTROL PROTOCOL (MAC): Definition : Types : Details
PURE ALOHA : MEDIUM ACCESS CONTROL PROTOCOL (MAC): Definition : Types : DetailsPURE ALOHA : MEDIUM ACCESS CONTROL PROTOCOL (MAC): Definition : Types : Details
PURE ALOHA : MEDIUM ACCESS CONTROL PROTOCOL (MAC): Definition : Types : Details
 
Carrier-sense multiple access with collision avoidance CSMA/CA
Carrier-sense multiple access with collision avoidance CSMA/CACarrier-sense multiple access with collision avoidance CSMA/CA
Carrier-sense multiple access with collision avoidance CSMA/CA
 
RFID (RADIO FREQUENCY IDENTIFICATION)
RFID (RADIO FREQUENCY IDENTIFICATION)RFID (RADIO FREQUENCY IDENTIFICATION)
RFID (RADIO FREQUENCY IDENTIFICATION)
 
SPACE DIVISION MULTIPLE ACCESS (SDMA) SATELLITE COMMUNICATION
SPACE DIVISION MULTIPLE ACCESS (SDMA) SATELLITE COMMUNICATION  SPACE DIVISION MULTIPLE ACCESS (SDMA) SATELLITE COMMUNICATION
SPACE DIVISION MULTIPLE ACCESS (SDMA) SATELLITE COMMUNICATION
 
Threads Basic : Features, Types & Implementation
Threads Basic : Features, Types  & ImplementationThreads Basic : Features, Types  & Implementation
Threads Basic : Features, Types & Implementation
 
CLOUD COMPUTING : BASIC CONCEPT REGARDING LOAD BALANCING AND Virtual Machine ...
CLOUD COMPUTING : BASIC CONCEPT REGARDING LOAD BALANCING AND Virtual Machine ...CLOUD COMPUTING : BASIC CONCEPT REGARDING LOAD BALANCING AND Virtual Machine ...
CLOUD COMPUTING : BASIC CONCEPT REGARDING LOAD BALANCING AND Virtual Machine ...
 
JavaScript with Syntax & Implementation
JavaScript with Syntax & ImplementationJavaScript with Syntax & Implementation
JavaScript with Syntax & Implementation
 

Recently uploaded

Current Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCLCurrent Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCLDeelipZope
 
Software Development Life Cycle By Team Orange (Dept. of Pharmacy)
Software Development Life Cycle By  Team Orange (Dept. of Pharmacy)Software Development Life Cycle By  Team Orange (Dept. of Pharmacy)
Software Development Life Cycle By Team Orange (Dept. of Pharmacy)Suman Mia
 
MANUFACTURING PROCESS-II UNIT-2 LATHE MACHINE
MANUFACTURING PROCESS-II UNIT-2 LATHE MACHINEMANUFACTURING PROCESS-II UNIT-2 LATHE MACHINE
MANUFACTURING PROCESS-II UNIT-2 LATHE MACHINESIVASHANKAR N
 
VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130
VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130
VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130Suhani Kapoor
 
High Profile Call Girls Nashik Megha 7001305949 Independent Escort Service Na...
High Profile Call Girls Nashik Megha 7001305949 Independent Escort Service Na...High Profile Call Girls Nashik Megha 7001305949 Independent Escort Service Na...
High Profile Call Girls Nashik Megha 7001305949 Independent Escort Service Na...Call Girls in Nagpur High Profile
 
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escortsranjana rawat
 
ZXCTN 5804 / ZTE PTN / ZTE POTN / ZTE 5804 PTN / ZTE POTN 5804 ( 100/200 GE Z...
ZXCTN 5804 / ZTE PTN / ZTE POTN / ZTE 5804 PTN / ZTE POTN 5804 ( 100/200 GE Z...ZXCTN 5804 / ZTE PTN / ZTE POTN / ZTE 5804 PTN / ZTE POTN 5804 ( 100/200 GE Z...
ZXCTN 5804 / ZTE PTN / ZTE POTN / ZTE 5804 PTN / ZTE POTN 5804 ( 100/200 GE Z...ZTE
 
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube ExchangerStudy on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube ExchangerAnamika Sarkar
 
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptxDecoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptxJoão Esperancinha
 
Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝
Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝
Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝soniya singh
 
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxMicroscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxpurnimasatapathy1234
 
Call Girls in Nagpur Suman Call 7001035870 Meet With Nagpur Escorts
Call Girls in Nagpur Suman Call 7001035870 Meet With Nagpur EscortsCall Girls in Nagpur Suman Call 7001035870 Meet With Nagpur Escorts
Call Girls in Nagpur Suman Call 7001035870 Meet With Nagpur EscortsCall Girls in Nagpur High Profile
 
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130Suhani Kapoor
 
Porous Ceramics seminar and technical writing
Porous Ceramics seminar and technical writingPorous Ceramics seminar and technical writing
Porous Ceramics seminar and technical writingrakeshbaidya232001
 
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICSAPPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICSKurinjimalarL3
 
Coefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptxCoefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptxAsutosh Ranjan
 
What are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxWhat are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxwendy cai
 
Call Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur Escorts
Call Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur EscortsCall Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur Escorts
Call Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur EscortsCall Girls in Nagpur High Profile
 

Recently uploaded (20)

Current Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCLCurrent Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCL
 
Software Development Life Cycle By Team Orange (Dept. of Pharmacy)
Software Development Life Cycle By  Team Orange (Dept. of Pharmacy)Software Development Life Cycle By  Team Orange (Dept. of Pharmacy)
Software Development Life Cycle By Team Orange (Dept. of Pharmacy)
 
MANUFACTURING PROCESS-II UNIT-2 LATHE MACHINE
MANUFACTURING PROCESS-II UNIT-2 LATHE MACHINEMANUFACTURING PROCESS-II UNIT-2 LATHE MACHINE
MANUFACTURING PROCESS-II UNIT-2 LATHE MACHINE
 
VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130
VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130
VIP Call Girls Service Kondapur Hyderabad Call +91-8250192130
 
High Profile Call Girls Nashik Megha 7001305949 Independent Escort Service Na...
High Profile Call Girls Nashik Megha 7001305949 Independent Escort Service Na...High Profile Call Girls Nashik Megha 7001305949 Independent Escort Service Na...
High Profile Call Girls Nashik Megha 7001305949 Independent Escort Service Na...
 
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
 
ZXCTN 5804 / ZTE PTN / ZTE POTN / ZTE 5804 PTN / ZTE POTN 5804 ( 100/200 GE Z...
ZXCTN 5804 / ZTE PTN / ZTE POTN / ZTE 5804 PTN / ZTE POTN 5804 ( 100/200 GE Z...ZXCTN 5804 / ZTE PTN / ZTE POTN / ZTE 5804 PTN / ZTE POTN 5804 ( 100/200 GE Z...
ZXCTN 5804 / ZTE PTN / ZTE POTN / ZTE 5804 PTN / ZTE POTN 5804 ( 100/200 GE Z...
 
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube ExchangerStudy on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
 
★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR
★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR
★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR
 
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptxDecoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
 
Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝
Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝
Model Call Girl in Narela Delhi reach out to us at 🔝8264348440🔝
 
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxMicroscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptx
 
Call Girls in Nagpur Suman Call 7001035870 Meet With Nagpur Escorts
Call Girls in Nagpur Suman Call 7001035870 Meet With Nagpur EscortsCall Girls in Nagpur Suman Call 7001035870 Meet With Nagpur Escorts
Call Girls in Nagpur Suman Call 7001035870 Meet With Nagpur Escorts
 
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
 
Porous Ceramics seminar and technical writing
Porous Ceramics seminar and technical writingPorous Ceramics seminar and technical writing
Porous Ceramics seminar and technical writing
 
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICSAPPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
 
Coefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptxCoefficient of Thermal Expansion and their Importance.pptx
Coefficient of Thermal Expansion and their Importance.pptx
 
DJARUM4D - SLOT GACOR ONLINE | SLOT DEMO ONLINE
DJARUM4D - SLOT GACOR ONLINE | SLOT DEMO ONLINEDJARUM4D - SLOT GACOR ONLINE | SLOT DEMO ONLINE
DJARUM4D - SLOT GACOR ONLINE | SLOT DEMO ONLINE
 
What are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxWhat are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptx
 
Call Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur Escorts
Call Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur EscortsCall Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur Escorts
Call Girls Service Nagpur Tanvi Call 7001035870 Meet With Nagpur Escorts
 

Traveling salesman problem: Game Scheduling Problem Solution: Ant Colony Optimization

  • 1. AssignmentNo.1 Findthe Shortesttourfrom the followinggraphusingACO-TSP(antColonyOptimization-Travelling SalesmanProblem) wherethe graphrepresentsasetof nodesanddistance betweeneverypairof nodes.The shortestpossibleroute mustvisit everynode exactlyonce andreturntothe startingpoint. (Assume startnode is1) Solution: Steps: 1. Considernode1asthe startingand endingpoint. 2. Generate all (n-1)!Permutationsof nodes. 3. Calculate costof everypermutationandkeeptrackof minimum costpermutation. 4. Returnthe permutationwithminimumcost. Sl No. Permutations Corresponding cost 1 1-2-3-4-1 95(10+35+30+20) 2 1-2-4-3-1 80(10+25+30+15) 3 1-3-2-4-1 95(15+35+25+20) 4 1-3-4-2-1 80(15+30+25+10) 5 1-4-3-2-1 95(20+30+35+10) 6 1-4-2-3-1 95(20+25+35+15)
  • 2. Weightage Matrix: 1 2 3 4 1 0 10 15 20 2 10 0 35 25 3 15 35 0 30 4 20 25 30 0 Let usassume,start node 1, considerasS Iteration No. Cost function Evaluation Cost Path 1 C(4,S) D(4,1) 20 1-4 C(3,S) D(3,1) 15 1-3 C(2,S) D(2,1) 10 1-2 2 C(2,{3}) D(2,3)+C(3,S) 35+15=50 1-3-2 C(2, {4}) D(2,4)+C(4,S) 25+20=45 1-4-2 C(3,{2}) D(3,2)+C(2,S) 35+10=45 1-2-3 C(3,{4}) D(3,4)+C(4,S) 30+20=50 1-4-3 C(4,{2}) D(4,2)+C(2,S) 25+10=35 1-2-4 C(4,{3}) D(4,3)+C(3,S) 30+15=45 1-3-4 3 C(2,{3,4}) MIN(D(2,3) + C(3,{4}), D(2,4)+C(4,{3})) MIN(50+35,45+25) =80 1-3-4-2 C(3,{2,4}) MIN(D(3,2)+C(2,{4}), D(3,4)+C(4,{2})) MIN(45+35,35+30) =65 1-2-4-3 C(4,{2,3}) MIN(D(4,2)+C(2,{3}), D(4,3)+C(3,{2})) MIN(50+25,45+30) =75 1-2-3-4 4 C(1,{2,3,4}) MIN(D(1,2)+C(2,{3,4}) , D(1,3)+C(3,{2,4}), D(1,4)+ C(4,{2,3})) MIN(90,80,95) =80 1-2-4-3-1 SO,THE OPTIMAL PATH 1-2-4-3-1 FOR TOUR HAS LENGTH 80. AssignmentNo.2 There are 5 teams:T1, T2, T3, T4 and T5 ina couple of serieswhere 3typesof games:G1, G2 and G3. NowT1 and T3 bothplaysall three typesof games,T2 playsonlyG1 and G3, T4 plays onlyG2 and G3 andT5 onlyplaysG1 and G3. NowusingAntColonyOptimizationfindoutthe schedulingof gamesamongG1,G2 and G3. Solution: Here create a matrix Cij where ithrepresentsteamandjthrepresentsgame.Now consider1 for playinggame and0 for non-playinggame.
  • 3. G1 G2 G3 T1 1 1 1 T2 1 0 1 T3 1 1 1 T4 0 1 1 T5 1 0 1 Now,the weightage Dij representsthe numberof competitorswherethe competitor participatesinboththe gamesI and j. Thisweightage functionformsamatrix whichisknownasweightage matrix. D3x3 G1 G2 G3 G1 0 2 4 G2 2 0 3 G3 4 3 0 SL NO PERMUTATION PATH COST 1 1-2-3-1 9 2 1-3-2-1 9 3 2-1-3-2 9 4 2-3-1-2 9 5 3-1-2-3 9 1 2 3 2 4 3
  • 4. 6 3-2-1-3 9 Let us assume start node 1 (S) IterationNo. Cost function Evaluation Cost Path 1 C(2,S) D(2,1) 2 1-2 C(3,S) D(3,1) 4 1-3 2 C(3,{2}) D(3,2)+C(2,S) 3+2=5 1-2-3 C(2,{3}) D(2,3)+C(3,S) 3+4=7 1-3-2 MIN(C(3,{2}),C(2,{3}))=MIN(5,7) =5 SO,PATH 1-2-3 Let us assume start node 2 (S) IterationNo. Cost function Evaluation Cost Path 1 C(1,S) D(1,2) 2 2-1 C(3,S) D(3,2) 3 2-3 2 C(3,{1}) D(3,1)+C(1,S) 4+2=6 2-1-3 C(1,{3}) D(1,3)+C(3,S) 4+3=7 2-3-1 MIN(C(3,{1}),C(1,{3}))=MIN(6,7) =6 SO,PATH 2-1-3 Let us assume start node 3 (S) IterationNo. Cost function Evaluation Cost Path 1 C(2,S) D(2,3) 3 3-2 C(1,S) D(1,3) 4 3-1 2 C(1,{2}) D(1,2)+C(2,S) 2+3=5 3-2-1 C(2,{1}) D(2,1)+C(1,S) 2+4=6 3-1-2 MIN(C(1,{2}),C(2,{1}))=MIN(5,6) =5 SO,PATH 3-2-1 So overall minimizationeitherpathschedule 1-2-3or 3-2-1 So,G1-G2-G3 OR G3-G2-G1.