'Feasible solutions' presentation slideshows

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Theory of Computing

Theory of Computing. Lecture 14 MAS 714 Hartmut Klauck. Linear Programming. Linear Programming is the most powerful optimization problem that can be solved in polynomial time Some generalizations [ semidefinite programming] can be much more appropriate to use Fast LP solvers exist

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Chapter 2. Optimal Trees and Paths

Chapter 2. Optimal Trees and Paths. Combinatorial Optimization 2012. 1. 2.1 Minimum Spanning Trees. Definitions about Graphs: graph , : set of nodes, : set of edges, relation associating with each edge a pair of its end nodes. simple graph : graph with no parallel edges, no loops

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Presenter: Masoud Mazloom 27 th Oct. 2010

A survey of Constraint Handling Techniques in Evolutionary Computation Methods Author: Zbigneiw Michalewicz. Presenter: Masoud Mazloom 27 th Oct. 2010. 1. Outline. Introduction Numerical Optimization and Unfeasible solutions : Nonlinear programming problem Constraint-handling methods:

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Enumerating, Sampling and Counting: some illustrative cases in biology

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Tetsuyuki TAKAHAMA ? Hiroshima City University ? Setsuko SAKAI ? Hiroshima Shudo University)

Constrained Optimization by the e Constrained Differential Evolution with an Archive and Gradient-Based Mutation. Tetsuyuki TAKAHAMA ? Hiroshima City University ? Setsuko SAKAI ? Hiroshima Shudo University). Outline. Constrained optimization problems The e constrained method

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Geometric Crossover for Permutations with Repetitions: Application to Graph Partitioning

PPSN 2006. Geometric Crossover for Permutations with Repetitions: Application to Graph Partitioning. A. Moraglio, Y-H. Kim, Y. Yoon, B-R. Moon & R. Poli. Contents. Geometric Crossover Geometric Crossover for Permutation with Repetitions Geometric Crossover for Graph Partitioning

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Resolution Based Search

Resolution Based Search. John Hooker GSIA Feb 2003. Previous Work. This talk generalizes & unifies contributions of: Gaschnig 1977 (backjumping, backmarking, backchecking) Ginsberg 1993 (dynamic backtracking) McAllester 1993 (partial order dynamic backtracking)

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P&T Company Distribution Problem

P&T Company Distribution Problem. Shipping Data. Current Shipping Plan. Shipping Cost per Truckload. Total shipping cost = 75($464) + 5($352) + 65($416) + 55($690) + 15($388) + 85($685) = $165,595. Terminology for a Transportation Problem. Characteristics of Transportation Problems.

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Rotational Ambiguity in Hard-Soft Modeling Method

Rotational Ambiguity in Hard-Soft Modeling Method. Hard-Soft Modeling.

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Approximation Algorithms

Approximation Algorithms. Duality My T. Thai @ UF. Duality. Given a primal problem: P: min c T x subject to Ax ? b, x ? 0 The dual is: D: max b T y subject to A T y ? c, y ? 0. An Example. Weak Duality Theorem. Weak duality Theorem:

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Lesson 7.6, page 767 Linear Programming

Lesson 7.6, page 767 Linear Programming. Objective : Write an objective function describing a quantity that must be maximized or minimized. Use inequalities to describe limitations in a situation. Use linear programming to solve problems. Linear Programming.

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GRAPHICAL REPRESENTATION

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Branch-and-bound

Branch-and-bound. Branch and Bound. An enhancement of backtracking Similarity A state space tree is used to solve a problem . Difference The branch-and-bound algorithm does not limit us to any particular way of traversing the tree and is used only for optimization problems

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INTRODUCTION TO OR AND FORMULATION OF LPP AND GRAPHICAL SOLUTION

INTRODUCTION TO OR AND FORMULATION OF LPP AND GRAPHICAL SOLUTION. TOPIC NO-1. DEFINITION, MEANING AND ORIGIN OF OR. WHAT IS OR ?. . OR STANDS FOR OPERATION RESEARCH. .IT WAS COINED BY Mc CLOSKY AND TREFTHEN IN 1940. .ORIGINATED DURING WW2 .

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Simplex Method for Bounded Variables

Simplex Method for Bounded Variables. Linear programming problems with lower and upper bounds Generalizing simplex algorithm for bounded variables Reference: Chapter 5 in Bazaraa, Jarvis, and Sherali. LP Problems with Bounded Variables.

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Utilizing Condor to Support Genetic Algorithm Design Research

Utilizing Condor to Support Genetic Algorithm Design Research. Mary Beth Kurz, PhD Assistant Professor Department of Industrial Engineering Clemson University. Genetic algorithms are metaheuristics for optimization. evaluation. Solution space. Objective space. Feasible solutions.

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WOOD 492 MODELLING FOR DECISION SUPPORT

WOOD 492 MODELLING FOR DECISION SUPPORT. Lecture 2 Introduction to Linear Programming. Last Class. Introduction to Operations Research Examples of OR in forestry Introduction to mathematical models Objective function, decision variables, constraints. Example: Custom Cabinets company.

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Find the vertices of the region.

COPY. ET 7.6. List the steps for solving a linear programming problem:. 1. Sketch the region corresponding to the system of constraints. The points inside or on the boundary of the region are the feasible solutions. 2. Find the vertices of the region.

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