'Maximization problem' diaporamas de présentation

Chapter 16

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OPERATIONS MANAGEMENT for MBAs

OPERATIONS MANAGEMENT for MBAs. Topic 5: Decision Making, Strategic Allocation of Resources, & Simulation. Outline. About the best alternative under various outcome scenarios. Break Even Analysis Preference Matrix Certainty Uncertainty Risk Expected Value Decision Trees

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CS38 Introduction to Algorithms

CS38 Introduction to Algorithms. Lecture 16 May 22, 2014. Outline. Linear programming LP duality e llipsoid algorithm * slides from Kevin Wayne coping with intractibility NP-completeness. LP Duality. Primal problem.

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Inductive Semi-supervised Learning

Inductive Semi-supervised Learning. Gholamreza Haffari Supervised by: Dr. Anoop Sarkar Simon Fraser University, School of Computing Science. Outline of the talk. Introduction to Semi-Supervised Learning (SSL) Classifier based methods EM

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Principal Components Analysis

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Decision Analysis-Decision Trees

Decision Analysis-Decision Trees. A decision tree is a graphical representation of every possible sequence of decision and random outcomes (states of nature) that can occur within a given decision making problem.

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Learning Objectives for Section 6.3

Learning Objectives for Section 6.3. Dual Problem: Minimization with Problem Constraints of the Form >. The student will be able to formulate the dual problem. The student will be able to solve minimization problems.

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Approximation Algorithms

ADVANCED TOPICS IN COMPLEXITY THEORY. Approximation Algorithms. Pages 365 - 367 . Optimization problems . Optimization problems - seek the best solution among a collection of possible solutions. Example: shortest path connecting two nodes

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Polynomial Time Approximation Schemes and Parameterized Complexity

Polynomial Time Approximation Schemes and Parameterized Complexity. Jianer Chen Texas A&M University. Joint work with Xiuzhen Huang, Ge Xia, and I. Kanj. Approximation Algorithms and Parameterized Algorithms. Assuming P ? NP

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Firefly Algorithm By Rasool Tavakoli

Firefly Algorithm By Rasool Tavakoli. Outline. Abstract Introduction Particle Swarm Optimization Firefly Algorithm Comparison of FA with PSO and GA Conclusions References. Abstract. Nature-inspired algorithms are among the most powerful algorithms for optimization.

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Transportation, Assignment, and Transshipment Problems

Transportation, Assignment, and Transshipment Problems. Chapter 7. Transportation, Assignment, and Transshipment Problems.

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Particle Swarm Optimization Algorithms to Continuous Problem

Particle Swarm Optimization Algorithms to Continuous Problem. Monday, March 10, 2014 by. Yoon-Teck Bau, Hong-Tat Ewe, Chin-Kuan Ho Faculty of Information Technology Multimedia University, Malaysia {ytbau, htewe, ckho}@mmu.edu.my http://pesona.mmu.edu.my/~ytbau/. Talk Outlines.

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Linear Fractional Programming

Linear Fractional Programming. What is LFP?. Minimize Subject to p,q are n vectors, b is an m vector, A is an m*n matrix, ?,? are scalar. Lemma 11.4.1. Let f(x)=(p t x+ ?)/(q t x+?), and let S be a convex set such that q t x+? ?0 over S.

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Monopoly

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WOOD 492 MODELLING FOR DECISION SUPPORT

WOOD 492 MODELLING FOR DECISION SUPPORT. Lecture 19 Branch and Bound Algorithm. IP Solution Approach. Solve the LP relaxation and round the answers Normally the rounded answers are not feasible, or are far from optimal Exhaustive search of all feasible points

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Theories in corporate finance and financial markets

Theories in corporate finance and financial markets. The Akerlof model (Nobel Prize Winner in Economic 2001).

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