'Integer programming problem' presentation slideshows

Transference Theorems in the Geometry of Numbers

Transference Theorems in the Geometry of Numbers. Daniel Dadush New York University. Convex Bodies. Convex body . (convex, full dimensional and bounded). Convexity: Line between and in . Equivalently . Non convex set. Integer Programming Problem (IP). Input:

1.64k views • 138 slides

Computational Challenges with Cliques, Quasi-Cliques and Clique Partitions in Graphs

Computational Challenges with Cliques, Quasi-Cliques and Clique Partitions in Graphs. Panos M. Pardalos. Notations. is a simple undirected graph with vertex set and . is the complement graph of where

1.58k views • 125 slides

Computational Methods for Management and Economics Carla Gomes

852 views • 68 slides

Constraint Satisfaction Problems & Constraint Programming Representing Knowledge with Constraints

Constraint Satisfaction Problems & Constraint Programming Representing Knowledge with Constraints . x 1. x 2. x 6. x 3. x 4. x 5. KR&R for Combinatorial Problems. Many, many practical applications

1.13k views • 67 slides

Solving Constraint Satisfaction and Optimization Problems with CLP(FD)

Solving Constraint Satisfaction and Optimization Problems with CLP(FD). Neng-Fa Zhou The City University of New York zhou@sci.brooklyn.cuny.edu. Outline of Lectures. Constraint Satisfaction Problems (CSPs) Constraint programming by example

639 views • 47 slides

Multiple Instance Learning for Sparse Positive Bags

Multiple Instance Learning for Sparse Positive Bags. Razvan C. Bunescu. Raymond J. Mooney. Machine Learning Group Department of Computer Sciences University of Texas at Austin. Machine Learning Group Department of Computer Sciences University of Texas at Austin. razvan@cs.utexas.edu.

585 views • 45 slides

Efficient algorithms for Web services selection with end-to-end QoS constraints

Efficient algorithms for Web services selection with end-to-end QoS constraints. ACM Transactions on the Web, Vol. 1, No. 1, Article 6, Publication date: May 2007 69721033 ???. Outline. Introduction System architecture Service selection algorithms for sequential flow structure

569 views • 38 slides

CSE 589 Part VI

CSE 589 Part VI. Reading. Skiena, Sections 5.5 and 6.8 CLR, chapter 37. Techniques for Dealing with NP-complete Problems. Exactly backtracking , branch and bound Approximately approximation algorithms with performance guarantees using LP (e.g., randomized rounding)

399 views • 33 slides

MIV Dependences

370 views • 25 slides

KUBO Mikio Tokyo University of Mercantile Marine Logistic and Information Engineering

The vender managed inventory system for vending machines and a two-phase algorithm for the inventory routing problem. KUBO Mikio Tokyo University of Mercantile Marine Logistic and Information Engineering. Joint Work with Fuji Electric.

377 views • 25 slides

Optimization Techniques

Optimization Techniques. Problem Description. Definition Modeling Solution algorithm. Problem Definition. Decision (independent) and dependent variables Constraints functions Objective functions. Solution Algorithms. Mathematical Techniques Heuristic Techniques.

518 views • 24 slides

MA/CSSE 473 Day 23

MA/CSSE 473 Day 23. Review of Binary Heaps and Heapsort Overview of what you should know about hashing Answers to student questions. Binary (max) Heap Quick Review. Representation change example. See also Weiss, Chapter 21 (Weiss does min heaps). An almost-complete Binary Tree

242 views • 24 slides

BA 555 Practical Business Analysis

BA 555 Practical Business Analysis. Agenda. Linear Programming (LP) Examples Integer Linear Programming Sensitivity Analysis. Decision-making under Uncertainty.

434 views • 23 slides

BA 555 Practical Business Analysis

BA 555 Practical Business Analysis. Agenda. Linear Programming (LP) Examples Integer Linear Programming Sensitivity Analysis. Decision-making under Uncertainty.

356 views • 23 slides

A Periodic Portfolio Scheduler for Scientific Computing in the Data Center

A Periodic Portfolio Scheduler for Scientific Computing in the Data Center. Kefeng Deng, Ruben Verboon , Kaijun Ren , and Alexandru Iosup Parallel and Distributed Systems Group. JSSSP, IPDPS WS, Boston, MA, USA May 24, 2013.

302 views • 22 slides

IBM Student Workshop for Frontiers of Cloud Computing 2011

IBM Student Workshop for Frontiers of Cloud Computing 2011.

268 views • 18 slides

Chapter 1. Introduction

Chapter 1. Introduction. Ex : Diet Problem Daily requirements : energy(2000kcal), protein(55g), calcium(800mg). Formulation:. Subject to. ????? ?? (LP problem). ? ???? (objective function). ???? (right hand side). Subject to. ??? (constraints). ????? (nonnegativity constraints).

152 views • 15 slides

Integer linear programming

Integer linear programming. Optimization problems where design variables have to be integers are more difficult than ones with continuous variables. The degree of difficulty is particularly damaging for large number of variables:

254 views • 7 slides