Lecture 17 Shortest Path Problem. October 18, 2009
|
|
|
- Alyson Robbins
- 9 years ago
- Views:
Transcription
1 Shortest Path Problem October 18, 2009
2 Outline Lecture 17 Network Models Minimal Spanning Tree Problem Shortest Route Problem - TODAY: modeling aspect Maximal-flow Problem Operations Research Methods 1
3 Lecture 17 Shortest Path Problem: Form Given a road network and a starting node s, we want to determine the shortest path to all the other nodes in the network (or to a specified destination node). This is Shortest Path Problem Note that the graph is directed. The weights on the links are costs. We consider several applications. Operations Research Methods 2
4 Example: Equipment Replacement RentCar is developing a replacement policy for its car fleet for a 4-year period. At the start of the first year, the RentCar must purchase a car. At the start of each subsequent year, a decision can be made as to keep a car or to replace it. The car has to be in service for at least 1 year and no more than 3 years. The replacement cost is shown in the table below as a function of the period when it is purchased and the years kept in operation. Years in operation Start of a year The problem is to determine the best decision that minimizes the total cost incurred over the period of 4 years. Operations Research Methods 3
5 All possible decisions Decision Cost Total Cost By a car in years 1,2,3, By a car in years 1,2, x By a car in years 1,2, x By a car in years 1,3, x By a car in years 1, x x By a car in years 1, x 7100 x By a car in years 1, x x The problem of determining the optimal decision can be formulated as shortest path! Operations Research Methods 4
6 The best decision corresponds to the shortest path from node 1 to node 5, which is with the cost of = This path corresponds to the decision of purchasing the car in years 1 and 3. Operations Research Methods 5
7 Most Reliable Route XY drives daily to work. There are several routes that XY can take. Each link is patrolled by police and for each link there is an estimated probability of not being stopped (see figure below). The reliability of a route is the product of the reliability of the links in the route. XY wants to drive fast (speeding) and maximize the probability of not being stopped by police. Operations Research Methods 6
8 Transform the problem to minimization form Let P be the set of all paths from node 1 to node 7. Let p P be a path. Let l p denote that link l is traversed in a path p. The maximum reliable route is the following problem max p P Π l pπ l By taking ln transformation of the objective, the problem is equivalent to max p P l p ln(π l ) (1) The problems are equivalent in the sense that their solutions are the same Operations Research Methods 7
9 The maximization of l p ln(π l ) over p P is equivalent to minimization of l p ln(π l ) over p P, i.e., the problem in (1) is equivalent to min p P l p ln(π l ) Again, the equivalence is in the sense that their optimal solutions are the same Thus the most reliable route can be found by finding the shortest route in the network, where a link reliability is replaced with ln of the reliability (see the network below). Operations Research Methods 8
10 The most reliable route of the original network is the shortest path in this network Operations Research Methods 9
11 Three-Jug Puzzle We have an 8-gallon jug filled with water. We also have two empty jugs, one 5-gallon and one 3-gallon. We want to divide 8 gallons of water into two 4-gallon parts using the three jugs. No other measuring devices are available. What is the smallest number of transfers needed to achieve the result? We can formulate the problem as shortest path. Construct a network with each node representing the amount of water in the jugs a node is an ordered tuple representing the amount of water in 8-gallon, 5-gallon, and 3-gallon jug. Place a link from node a to node b when it is possible to move from node a to node b in one transfer (i.e, by pouring water from one jug to another jug) Operations Research Methods 10
12 Operations Research Methods 11
13 Operations Research Methods 12
14 Each link counts for one transfer. Assign cost of 1 to each link, and find the shortest path from node (8,0,0) to (4,4,0). The shortest path is shown below. The minimal number of transfers is 7. Operations Research Methods 13
( ) = ( ) = {,,, } β ( ), < 1 ( ) + ( ) = ( ) + ( )
{ } ( ) = ( ) = {,,, } ( ) β ( ), < 1 ( ) + ( ) = ( ) + ( ) max, ( ) [ ( )] + ( ) [ ( )], [ ( )] [ ( )] = =, ( ) = ( ) = 0 ( ) = ( ) ( ) ( ) =, ( ), ( ) =, ( ), ( ). ln ( ) = ln ( ). + 1 ( ) = ( ) Ω[ (
Week_11: Network Models
Week_11: Network Models 1 1.Introduction The network models include the traditional applications of finding the most efficient way to link a number of locations directly or indirectly, finding the shortest
Social Media Mining. Graph Essentials
Graph Essentials Graph Basics Measures Graph and Essentials Metrics 2 2 Nodes and Edges A network is a graph nodes, actors, or vertices (plural of vertex) Connections, edges or ties Edge Node Measures
8.1 Min Degree Spanning Tree
CS880: Approximations Algorithms Scribe: Siddharth Barman Lecturer: Shuchi Chawla Topic: Min Degree Spanning Tree Date: 02/15/07 In this lecture we give a local search based algorithm for the Min Degree
Midterm Practice Problems
6.042/8.062J Mathematics for Computer Science October 2, 200 Tom Leighton, Marten van Dijk, and Brooke Cowan Midterm Practice Problems Problem. [0 points] In problem set you showed that the nand operator
Operations: search;; min;; max;; predecessor;; successor. Time O(h) with h height of the tree (more on later).
Binary search tree Operations: search;; min;; max;; predecessor;; successor. Time O(h) with h height of the tree (more on later). Data strutcure fields usually include for a given node x, the following
6.231 Dynamic Programming and Stochastic Control Fall 2008
MIT OpenCourseWare http://ocw.mit.edu 6.231 Dynamic Programming and Stochastic Control Fall 2008 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. 6.231
An Improved ACO Algorithm for Multicast Routing
An Improved ACO Algorithm for Multicast Routing Ziqiang Wang and Dexian Zhang School of Information Science and Engineering, Henan University of Technology, Zheng Zhou 450052,China [email protected]
Dynamic Programming 11.1 AN ELEMENTARY EXAMPLE
Dynamic Programming Dynamic programming is an optimization approach that transforms a complex problem into a sequence of simpler problems; its essential characteristic is the multistage nature of the optimization
Outline. IEEM241 Routing and Fleet Management. Course - Objectives. Background. Course summary Essence of decision models Decision models - examples
Outline IEEM241 Routing and Fleet Management Course summary Essence of decision models Decision models - examples Raymond Cheung Spring 2005 Course - Objectives Learn how to model decision problems in
Lecture 3. Linear Programming. 3B1B Optimization Michaelmas 2015 A. Zisserman. Extreme solutions. Simplex method. Interior point method
Lecture 3 3B1B Optimization Michaelmas 2015 A. Zisserman Linear Programming Extreme solutions Simplex method Interior point method Integer programming and relaxation The Optimization Tree Linear Programming
On the effect of forwarding table size on SDN network utilization
IBM Haifa Research Lab On the effect of forwarding table size on SDN network utilization Rami Cohen IBM Haifa Research Lab Liane Lewin Eytan Yahoo Research, Haifa Seffi Naor CS Technion, Israel Danny Raz
Question 1. [7 points] Consider the following scenario and assume host H s routing table is the one given below:
Computer Networks II Master degree in Computer Engineering Exam session: 11/02/2009 Teacher: Emiliano Trevisani Last name First name Student Identification number You are only allowed to use a pen and
Ring Protection: Wrapping vs. Steering
Ring Protection: Wrapping vs. Steering Necdet Uzun and Pinar Yilmaz March 13, 2001 Contents Objectives What are wrapping and steering Single/dual fiber cut Comparison of wrapping and steering Simulation
Oracle Spatial and Graph. Jayant Sharma Director, Product Management
Oracle Spatial and Graph Jayant Sharma Director, Product Management Agenda Oracle Spatial and Graph Graph Capabilities Q&A 2 Oracle Spatial and Graph Complete Open Integrated Most Widely Used 3 Open and
Chapter 6: Graph Theory
Chapter 6: Graph Theory Graph theory deals with routing and network problems and if it is possible to find a best route, whether that means the least expensive, least amount of time or the least distance.
Analysis of Algorithms I: Binary Search Trees
Analysis of Algorithms I: Binary Search Trees Xi Chen Columbia University Hash table: A data structure that maintains a subset of keys from a universe set U = {0, 1,..., p 1} and supports all three dictionary
Graph Theory and Complex Networks: An Introduction. Chapter 06: Network analysis
Graph Theory and Complex Networks: An Introduction Maarten van Steen VU Amsterdam, Dept. Computer Science Room R4.0, [email protected] Chapter 06: Network analysis Version: April 8, 04 / 3 Contents Chapter
CSE331: Introduction to Networks and Security. Lecture 8 Fall 2006
CSE331: Introduction to Networks and Security Lecture 8 Fall 2006 Announcements Reminders: Project I is due on Monday, Sept. 25th. Homework 1 is due on Friday, Sept. 29th. CSE331 Fall 2004 2 Internet Protocol
Strategic Deployment in Graphs. 1 Introduction. v 1 = v s. v 2. v 4. e 1. e 5 25. e 3. e 2. e 4
Informatica 39 (25) 237 247 237 Strategic Deployment in Graphs Elmar Langetepe and Andreas Lenerz University of Bonn, Department of Computer Science I, Germany Bernd Brüggemann FKIE, Fraunhofer-Institute,
Load Balancing. Load Balancing 1 / 24
Load Balancing Backtracking, branch & bound and alpha-beta pruning: how to assign work to idle processes without much communication? Additionally for alpha-beta pruning: implementing the young-brothers-wait
2004 Networks UK Publishers. Reprinted with permission.
Riikka Susitaival and Samuli Aalto. Adaptive load balancing with OSPF. In Proceedings of the Second International Working Conference on Performance Modelling and Evaluation of Heterogeneous Networks (HET
Approximation Algorithms
Approximation Algorithms or: How I Learned to Stop Worrying and Deal with NP-Completeness Ong Jit Sheng, Jonathan (A0073924B) March, 2012 Overview Key Results (I) General techniques: Greedy algorithms
DESIGNING SERVICE FOR HUB-AND-SPOKE NETWORK
DESIGNING SERVICE FOR HUB-AND-SPOKE NETWORK Readings: J. Braklow, W. Graham, S. Hassler, K. Peck and W. Powell. Interactive Optimization Improves Service and Performance for Yellow Freight System. Interfaces
LOAD BALANCING IN WDM NETWORKS THROUGH DYNAMIC ROUTE CHANGES
LOAD BALANCING IN WDM NETWORKS THROUGH DYNAMIC ROUTE CHANGES S.Ramanathan 1, G.Karthik 1, Ms.G.Sumathi 2 1 Dept. of computer science Sri Venkateswara College of engineering, Sriperumbudur, 602 105. 2 Asst.professor,
HYBRID ACO-IWD OPTIMIZATION ALGORITHM FOR MINIMIZING WEIGHTED FLOWTIME IN CLOUD-BASED PARAMETER SWEEP EXPERIMENTS
HYBRID ACO-IWD OPTIMIZATION ALGORITHM FOR MINIMIZING WEIGHTED FLOWTIME IN CLOUD-BASED PARAMETER SWEEP EXPERIMENTS R. Angel Preethima 1, Margret Johnson 2 1 Student, Computer Science and Engineering, Karunya
DATA ANALYSIS IN PUBLIC SOCIAL NETWORKS
International Scientific Conference & International Workshop Present Day Trends of Innovations 2012 28 th 29 th May 2012 Łomża, Poland DATA ANALYSIS IN PUBLIC SOCIAL NETWORKS Lubos Takac 1 Michal Zabovsky
Clustering UE 141 Spring 2013
Clustering UE 141 Spring 013 Jing Gao SUNY Buffalo 1 Definition of Clustering Finding groups of obects such that the obects in a group will be similar (or related) to one another and different from (or
CAB TRAVEL TIME PREDICTI - BASED ON HISTORICAL TRIP OBSERVATION
CAB TRAVEL TIME PREDICTI - BASED ON HISTORICAL TRIP OBSERVATION N PROBLEM DEFINITION Opportunity New Booking - Time of Arrival Shortest Route (Distance/Time) Taxi-Passenger Demand Distribution Value Accurate
CSE 326, Data Structures. Sample Final Exam. Problem Max Points Score 1 14 (2x7) 2 18 (3x6) 3 4 4 7 5 9 6 16 7 8 8 4 9 8 10 4 Total 92.
Name: Email ID: CSE 326, Data Structures Section: Sample Final Exam Instructions: The exam is closed book, closed notes. Unless otherwise stated, N denotes the number of elements in the data structure
Load balancing Static Load Balancing
Chapter 7 Load Balancing and Termination Detection Load balancing used to distribute computations fairly across processors in order to obtain the highest possible execution speed. Termination detection
Load Balancing and Termination Detection
Chapter 7 Load Balancing and Termination Detection 1 Load balancing used to distribute computations fairly across processors in order to obtain the highest possible execution speed. Termination detection
Lecture 8: Routing I Distance-vector Algorithms. CSE 123: Computer Networks Stefan Savage
Lecture 8: Routing I Distance-vector Algorithms CSE 3: Computer Networks Stefan Savage This class New topic: routing How do I get there from here? Overview Routing overview Intra vs. Inter-domain routing
Scheduling Shop Scheduling. Tim Nieberg
Scheduling Shop Scheduling Tim Nieberg Shop models: General Introduction Remark: Consider non preemptive problems with regular objectives Notation Shop Problems: m machines, n jobs 1,..., n operations
CS 3251- Computer Networks 1: Routing Algorithms
CS 35- Computer Networks : Routing Algorithms Professor Patrick Tranor 0//3 Lecture 3 Reminders The due date for Homework was moved to Thursda. Reason: Allow ou to attend toda s lecture. Project is still
Branch-and-Price Approach to the Vehicle Routing Problem with Time Windows
TECHNISCHE UNIVERSITEIT EINDHOVEN Branch-and-Price Approach to the Vehicle Routing Problem with Time Windows Lloyd A. Fasting May 2014 Supervisors: dr. M. Firat dr.ir. M.A.A. Boon J. van Twist MSc. Contents
Intrusion Detection: Game Theory, Stochastic Processes and Data Mining
Intrusion Detection: Game Theory, Stochastic Processes and Data Mining Joseph Spring 7COM1028 Secure Systems Programming 1 Discussion Points Introduction Firewalls Intrusion Detection Schemes Models Stochastic
Computer Networks II Master degree in Computer Engineering Exam session: 11/02/2009 Teacher: Emiliano Trevisani. Student Identification number
Computer Networks II Master degree in Computer Engineering Exam session: 11/02/2009 Teacher: Emiliano Trevisani Last name First name Student Identification number You are only allowed to use a pen and
Scheduling Home Health Care with Separating Benders Cuts in Decision Diagrams
Scheduling Home Health Care with Separating Benders Cuts in Decision Diagrams André Ciré University of Toronto John Hooker Carnegie Mellon University INFORMS 2014 Home Health Care Home health care delivery
KTH Challenge 2013. Solutions. Further Information KTH Challenge 2013. April 21, 2013
April 21, Jury Lukáš Poláček (, Spotify), head of jury Per Austrin () Oskar Werkelin Ahlin (Spotify) Ulf Lundström () Marc Vinyals () Erik Aas () Emma Enström () Andreas Lundblad () B Peragrams Only one
Bicolored Shortest Paths in Graphs with Applications to Network Overlay Design
Bicolored Shortest Paths in Graphs with Applications to Network Overlay Design Hongsik Choi and Hyeong-Ah Choi Department of Electrical Engineering and Computer Science George Washington University Washington,
Dynamic programming formulation
1.24 Lecture 14 Dynamic programming: Job scheduling Dynamic programming formulation To formulate a problem as a dynamic program: Sort by a criterion that will allow infeasible combinations to be eli minated
A Labeling Algorithm for the Maximum-Flow Network Problem
A Labeling Algorithm for the Maximum-Flow Network Problem Appendix C Network-flow problems can be solved by several methods. In Chapter 8 we introduced this topic by exploring the special structure of
How To Solve The Line Connectivity Problem In Polynomatix
Konrad-Zuse-Zentrum für Informationstechnik Berlin Takustraße 7 D-14195 Berlin-Dahlem Germany RALF BORNDÖRFER MARIKA NEUMANN MARC E. PFETSCH The Line Connectivity Problem Supported by the DFG Research
A hierarchical multicriteria routing model with traffic splitting for MPLS networks
A hierarchical multicriteria routing model with traffic splitting for MPLS networks João Clímaco, José Craveirinha, Marta Pascoal jclimaco@inesccpt, jcrav@deecucpt, marta@matucpt University of Coimbra
Graph Theory and Complex Networks: An Introduction. Chapter 06: Network analysis. Contents. Introduction. Maarten van Steen. Version: April 28, 2014
Graph Theory and Complex Networks: An Introduction Maarten van Steen VU Amsterdam, Dept. Computer Science Room R.0, [email protected] Chapter 0: Version: April 8, 0 / Contents Chapter Description 0: Introduction
Graph Theory and Complex Networks: An Introduction. Chapter 08: Computer networks
Graph Theory and Complex Networks: An Introduction Maarten van Steen VU Amsterdam, Dept. Computer Science Room R4.20, [email protected] Chapter 08: Computer networks Version: March 3, 2011 2 / 53 Contents
1.204 Lecture 10. Greedy algorithms: Job scheduling. Greedy method
1.204 Lecture 10 Greedy algorithms: Knapsack (capital budgeting) Job scheduling Greedy method Local improvement method Does not look at problem globally Takes best immediate step to find a solution Useful
Lecture 2.1 : The Distributed Bellman-Ford Algorithm. Lecture 2.2 : The Destination Sequenced Distance Vector (DSDV) protocol
Lecture 2 : The DSDV Protocol Lecture 2.1 : The Distributed Bellman-Ford Algorithm Lecture 2.2 : The Destination Sequenced Distance Vector (DSDV) protocol The Routing Problem S S D D The routing problem
Classification/Decision Trees (II)
Classification/Decision Trees (II) Department of Statistics The Pennsylvania State University Email: [email protected] Right Sized Trees Let the expected misclassification rate of a tree T be R (T ).
Reinforcement Learning
Reinforcement Learning LU 2 - Markov Decision Problems and Dynamic Programming Dr. Martin Lauer AG Maschinelles Lernen und Natürlichsprachliche Systeme Albert-Ludwigs-Universität Freiburg [email protected]
Chinese postman problem
PTR hinese postman problem Learning objectives fter studying this chapter, you should be able to: understand the hinese postman problem apply an algorithm to solve the problem understand the importance
ENTRANCE EXAMINATION FOR THE BACHELOR OF ENGINEERING DEGREE PROGRAMMES
ENTRANCE EXAMINATION FOR THE BACHELOR OF ENGINEERING DEGREE PROGRAMMES INSTRUCTIONS The Entrance Examination consists of three parts: Problem Solving (Part 1), Questions on Motivation (Part ), English
Cpt S 223. School of EECS, WSU
The Shortest Path Problem 1 Shortest-Path Algorithms Find the shortest path from point A to point B Shortest in time, distance, cost, Numerous applications Map navigation Flight itineraries Circuit wiring
Lecture 10 Scheduling 1
Lecture 10 Scheduling 1 Transportation Models -1- large variety of models due to the many modes of transportation roads railroad shipping airlines as a consequence different type of equipment and resources
THE last two decades have witnessed an exponential
IEEE JSAC - SAMPLING 2006 1 Practical Beacon Placement for Link Monitoring Using Network Tomography Ritesh Kumar and Jasleen Kaur Abstract Recent interest in using tomography for network monitoring has
Level 2 Routing: LAN Bridges and Switches
Level 2 Routing: LAN Bridges and Switches Norman Matloff University of California at Davis c 2001, N. Matloff September 6, 2001 1 Overview In a large LAN with consistently heavy traffic, it may make sense
Y. Xiang, Constraint Satisfaction Problems
Constraint Satisfaction Problems Objectives Constraint satisfaction problems Backtracking Iterative improvement Constraint propagation Reference Russell & Norvig: Chapter 5. 1 Constraints Constraints are
WAN Wide Area Networks. Packet Switch Operation. Packet Switches. COMP476 Networked Computer Systems. WANs are made of store and forward switches.
Routing WAN Wide Area Networks WANs are made of store and forward switches. To there and back again COMP476 Networked Computer Systems A packet switch with two types of I/O connectors: one type is used
Distributed Computing over Communication Networks: Topology. (with an excursion to P2P)
Distributed Computing over Communication Networks: Topology (with an excursion to P2P) Some administrative comments... There will be a Skript for this part of the lecture. (Same as slides, except for today...
4 UNIT FOUR: Transportation and Assignment problems
4 UNIT FOUR: Transportation and Assignment problems 4.1 Objectives By the end of this unit you will be able to: formulate special linear programming problems using the transportation model. define a balanced
Outline. NP-completeness. When is a problem easy? When is a problem hard? Today. Euler Circuits
Outline NP-completeness Examples of Easy vs. Hard problems Euler circuit vs. Hamiltonian circuit Shortest Path vs. Longest Path 2-pairs sum vs. general Subset Sum Reducing one problem to another Clique
Minimum cost maximum flow, Minimum cost circulation, Cost/Capacity scaling
6.854 Advanced Algorithms Lecture 16: 10/11/2006 Lecturer: David Karger Scribe: Kermin Fleming and Chris Crutchfield, based on notes by Wendy Chu and Tudor Leu Minimum cost maximum flow, Minimum cost circulation,
Graph Theory Algorithms for Mobile Ad Hoc Networks
Informatica 36 (2012) 185-200 185 Graph Theory Algorithms for Mobile Ad Hoc Networks Natarajan Meghanathan Department of Computer Science, Jackson State University Jackson, MS 39217, USA E-mail: [email protected]
Section #6: Addressing
Section #6: Addressing Problem 1: Routing entries Consider the following routing table for router A, given in CIDR ( slash-n ) notation: 56.162.0.0/15: Port 0 56.164.0.0/15: Port 1 56.166.0.0/16: Port
A Column Generation Model for Truck Routing in the Chilean Forest Industry
A Column Generation Model for Truck Routing in the Chilean Forest Industry Pablo A. Rey Escuela de Ingeniería Industrial, Facultad de Ingeniería, Universidad Diego Portales, Santiago, Chile, e-mail: [email protected]
3. The Junction Tree Algorithms
A Short Course on Graphical Models 3. The Junction Tree Algorithms Mark Paskin [email protected] 1 Review: conditional independence Two random variables X and Y are independent (written X Y ) iff p X ( )
Basic Components of an LP:
1 Linear Programming Optimization is an important and fascinating area of management science and operations research. It helps to do less work, but gain more. Linear programming (LP) is a central topic
Introduction to LAN/WAN. Network Layer
Introduction to LAN/WAN Network Layer Topics Introduction (5-5.1) Routing (5.2) (The core) Internetworking (5.5) Congestion Control (5.3) Network Layer Design Isues Store-and-Forward Packet Switching Services
6.02 Practice Problems: Routing
1 of 9 6.02 Practice Problems: Routing IMPORTANT: IN ADDITION TO THESE PROBLEMS, PLEASE SOLVE THE PROBLEMS AT THE END OF CHAPTERS 17 AND 18. Problem 1. Consider the following networks: network I (containing
Exercises Software Development I. 11 Recursion, Binary (Search) Trees. Towers of Hanoi // Tree Traversal. January 16, 2013
Exercises Software Development I 11 Recursion, Binary (Search) Trees Towers of Hanoi // Tree Traversal January 16, 2013 Software Development I Winter term 2012/2013 Institute for Pervasive Computing Johannes
The Goldberg Rao Algorithm for the Maximum Flow Problem
The Goldberg Rao Algorithm for the Maximum Flow Problem COS 528 class notes October 18, 2006 Scribe: Dávid Papp Main idea: use of the blocking flow paradigm to achieve essentially O(min{m 2/3, n 1/2 }
From Last Time: Remove (Delete) Operation
CSE 32 Lecture : More on Search Trees Today s Topics: Lazy Operations Run Time Analysis of Binary Search Tree Operations Balanced Search Trees AVL Trees and Rotations Covered in Chapter of the text From
MEI Structured Mathematics. Practice Comprehension Task - 2. Do trains run late?
MEI Structured Mathematics Practice Comprehension Task - 2 Do trains run late? There is a popular myth that trains always run late. Actually this is far from the case. All train companies want their trains
Introduction to IP v6
IP v 1-3: defined and replaced Introduction to IP v6 IP v4 - current version; 20 years old IP v5 - streams protocol IP v6 - replacement for IP v4 During developments it was called IPng - Next Generation
Binary Search Trees. A Generic Tree. Binary Trees. Nodes in a binary search tree ( B-S-T) are of the form. P parent. Key. Satellite data L R
Binary Search Trees A Generic Tree Nodes in a binary search tree ( B-S-T) are of the form P parent Key A Satellite data L R B C D E F G H I J The B-S-T has a root node which is the only node whose parent
Integrated Backup Topology Control and Routing of Obscured Traffic in Hybrid RF/FSO Networks*
Integrated Backup Topology Control and Routing of Obscured Traffic in Hybrid RF/FSO Networks* Abhishek Kashyap, Anuj Rawat and Mark Shayman Department of Electrical and Computer Engineering, University
2.3 Convex Constrained Optimization Problems
42 CHAPTER 2. FUNDAMENTAL CONCEPTS IN CONVEX OPTIMIZATION Theorem 15 Let f : R n R and h : R R. Consider g(x) = h(f(x)) for all x R n. The function g is convex if either of the following two conditions
SIMS 255 Foundations of Software Design. Complexity and NP-completeness
SIMS 255 Foundations of Software Design Complexity and NP-completeness Matt Welsh November 29, 2001 [email protected] 1 Outline Complexity of algorithms Space and time complexity ``Big O'' notation Complexity
MATH 304 Linear Algebra Lecture 9: Subspaces of vector spaces (continued). Span. Spanning set.
MATH 304 Linear Algebra Lecture 9: Subspaces of vector spaces (continued). Span. Spanning set. Vector space A vector space is a set V equipped with two operations, addition V V (x,y) x + y V and scalar
CS104: Data Structures and Object-Oriented Design (Fall 2013) October 24, 2013: Priority Queues Scribes: CS 104 Teaching Team
CS104: Data Structures and Object-Oriented Design (Fall 2013) October 24, 2013: Priority Queues Scribes: CS 104 Teaching Team Lecture Summary In this lecture, we learned about the ADT Priority Queue. A
CompSci-61B, Data Structures Final Exam
Your Name: CompSci-61B, Data Structures Final Exam Your 8-digit Student ID: Your CS61B Class Account Login: This is a final test for mastery of the material covered in our labs, lectures, and readings.
Chapter 15: Dynamic Programming
Chapter 15: Dynamic Programming Dynamic programming is a general approach to making a sequence of interrelated decisions in an optimum way. While we can describe the general characteristics, the details
IE 680 Special Topics in Production Systems: Networks, Routing and Logistics*
IE 680 Special Topics in Production Systems: Networks, Routing and Logistics* Rakesh Nagi Department of Industrial Engineering University at Buffalo (SUNY) *Lecture notes from Network Flows by Ahuja, Magnanti
International Journal of Software and Web Sciences (IJSWS) www.iasir.net
International Association of Scientific Innovation and Research (IASIR) (An Association Unifying the Sciences, Engineering, and Applied Research) ISSN (Print): 2279-0063 ISSN (Online): 2279-0071 International
Supporting Differentiated QoS in MPLS Networks
Supporting Differentiated QoS in MPLS Networks Roberto A. Dias 1, Eduardo Camponogara 2, and Jean-Marie Farines 2 1 Federal Technology Center of Santa Catarina, Florianópolis, 88020-300, Brazil 2 Federal
