'Combinatorial optimization problems' presentation slideshows

EXTREMAL VALUES OF TOLERANCES IN COMBINATORIAL OPTIMIZATION

EXTREMAL VALUES OF TOLERANCES IN COMBINATORIAL OPTIMIZATION. Boris Goldengorin Nizhny Novgorod Branch of Higher School of Economics, Russian Federation and University of Groningen, The Netherlands. Outline of this Talk. Elementary introduction Sensitivity analysis and tolerances

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Quadratic Assignment Problem (QAP)

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Modeling Rich Vehicle Routing Problems

Modeling Rich Vehicle Routing Problems. TIEJ601 Postgraduate Seminar Tuukka Puranen October 19 th 2009. Contents. A tour on combinatorial optimization problems relevant to logistics design Vehicle Routing Problem and its variants The proposed model for VRP Analysis

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Submodular Function Minimization

Submodular Function Minimization . Collette Coullard IMA and Northwestern University November 25, 2002. Outline. Introduction to Submodular Function Minimization (SFM) Definitions Applications- Why is SFM interesting? History Separation-optimization equivalence Developments

631 views • 34 slides

An Overview of Swarm Intelligence and Ant Colony Optimization Heuristics

An Overview of Swarm Intelligence and Ant Colony Optimization Heuristics. Philipp A. Djang Ph.D. Army Research Labs.

611 views • 31 slides

Different Local Search Algorithms in STAGE for Solving Bin Packing Problem

Different Local Search Algorithms in STAGE for Solving Bin Packing Problem. Gholamreza Haffari Sharif University of Technology haffari@ce.sharif.edu. Overview. Combinatorial Optimization Problems and State Spaces STAGE Algorithm Local Search Algorithms Results Conclusion and Future works.

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Ant Colony Optimization (ACO): Applications to Scheduling

Ant Colony Optimization (ACO): Applications to Scheduling. Franco Villongco IEOR 4405 4/28/09. Definition. Metaheuristic: similar to genetic algorithms, simulated annealing etc. Flexible enough to be applied to combinatorial optimization problems. Inspiration.

611 views • 17 slides

Simulated Annealing

Simulated Annealing. Van Laarhoven, Aarts Version 1, October 2000. Iterative Improvement 1. General method to solve combinatorial optimization problems Principle: Start with initial configuration Repeatedly search neighborhood and select a neighbor as candidate

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Research group on Logistics and International Business

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Combinatorial Optimization

Combinatorial Optimization. Chapter 8 Luke, Essentials of Metaheuristics, 2011 Byung-Hyun Ha. R2. Outline. Introduction Greedy Randomized Adaptive Search Procedures (GRASP) Ant Colony Optimization (ACO) Guided Local Search (GLS) Summary. Introduction. Combinatorial optimization

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CSE 3101

CSE 3101. Prof. Andy Mirzaian. Greedy Algorithms. STUDY MATERIAL:. [CLRS] chapter 16 Lecture Notes 7, 8. TOPICS. Combinatorial Optimization Problems The Greedy Method Problems: Coin Change Making Event Scheduling Interval Point Cover

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