'Local search methods' diaporamas de présentation

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Constraint Satisfaction

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Local and Stochastic Search

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CS 188: Artificial Intelligence Spring 2006

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Random 3-SAT

Random 3-SAT. Random 3-SAT sample uniformly from space of all possible 3-clauses n variables, l clauses Which are the hard instances? around l/n = 4.3. slide thanks to Henry Kautz. Random 3-SAT. Varying problem size, n Complexity peak appears to be largely invariant of algorithm

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Announcements

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Effective gradient-free methods for inverse problems

Effective gradient-free methods for inverse problems. Jyri Leskinen FiDiPro DESIGN project. Introduction. Current research Evolutionary algorithms Inverse problems Case study: Electrical Impedance Tomography (EIT) Future. Current research. Inverse problems Shape reconstruction

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Automated Guided Vehicle Optimal Control Problem

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Solutions for Scheduling Assays

Solutions for Scheduling Assays. Improve quality control (QC) Free resources Reduce sa fety risks Automatic data handling Increase sample throughput. Why do we use laboratory automation?. Scheduling Example. Sequential Processing. Running - Wash. Input. Output. Running - Dispense.

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Foundations of AI

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Constraint Propagation as the Core of Local Search

Constraint Propagation as the Core of Local Search. Nikolaos Pothitos, George Kastrinis, Panagiotis Stamatopoulos Department of Informatics and Telecommunications University of Athens. Constraint Propagation as the Core of Local Search 1 /20.

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Introduction to Job Shop Scheduling Problem

Introduction to Job Shop Scheduling Problem. Qianjun Xu Oct. 30, 2001. Description of Job Shop Scheduling. A finite set of n jobs Each job consists of a chain of operations A finite set of m machines Each machine can handle at most one operation at a time

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Introduction to Job Shop Scheduling Problem

Introduction to Job Shop Scheduling Problem. Qianjun Xu Oct. 30, 2001. Description of Job Shop Scheduling. A finite set of n jobs Each job consists of a chain of operations A finite set of m machines Each machine can handle at most one operation at a time

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Local Search Methods

Local Search Methods. Applicable when seeking Goal State & don't care how to get there. E.g., N-queens, map coloring, finding shortest/cheapest round trips (TSP, VRP) VLSI layout, planning, scheduling, time-tabling, . . . resource allocation protein structure prediction

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