'Objective functions' presentation slideshows

Multidisciplinary Design Optimisation of Unmanned Aerial Vehicles (UAV) using Multi-Criteria Evolutionary Algorithms

981 views • 55 slides

Overload Scheduling in Real-Time Systems

506 views • 40 slides

Cost-aware Pareto Optimal Test Suite Minimisation for Service-centric Systems

Cost-aware Pareto Optimal Test Suite Minimisation for Service-centric Systems. Mustafa Bozkurt CREST, University College London. Services Market. Gartner estimated Software as a Service (SaaS) and cloud-based business application services market as

501 views • 39 slides

Clustering III

Clustering III. Lecture outline. Soft (model-based) clustering and EM algorithm Clustering aggregation [A. Gionis, H. Mannila, P. Tsaparas: Clustering aggregation, ICDE 2004] Impossibility theorem for clustering [Jon Kleinberg, An impossibility theorem for clustering, NIPS 2002].

660 views • 38 slides

Fish 558 - Fall 2013 Decision Analysis in Natural Resource Management

Fish 558 - Fall 2013 Decision Analysis in Natural Resource Management. Basic Information. Instructor: Dr Andre Punt (FISH 116A; aepunt@u ) Office hours: Class web-site http://courses.washington.edu/fish558/ Prerequisites for this course Fish 458 (or talk to me)

419 views • 32 slides

International (fisheries) agreements and game theory

International (fisheries) agreements and game theory. Why is international fisheries management important? What are the major international agreements governing the exploitation of marine fisheries? An example of failure

488 views • 31 slides

Presentation of the tasks and activity planning for the work group BioMA

Presentation of the tasks and activity planning for the work group BioMA WP 3: BioMA (Multi-model crop yield estimates) Roberto Confalonieri & Marcello Donatelli roberto.confalonieri@unimi.it - www.robertoconfalonieri.it. E-AGRI kick-off meeting, 24-25 March 2011, VITO (Mol, Belgium).

428 views • 30 slides

Kyle M. Tarplee 1 , Ryan Friese 1 , Anthony A. Maciejewski 1 , H.J. Siegel 1,2

Efficient and Scalable Computation of the Energy and Makespan Pareto Front for Heterogeneous Computing Systems. Kyle M. Tarplee 1 , Ryan Friese 1 , Anthony A. Maciejewski 1 , H.J. Siegel 1,2 1 Department of Electrical and Computer Engineering 2 Department of Computer Science

370 views • 25 slides

Multilevel Generalized Force-directed Method for Circuit Placement

Multilevel Generalized Force-directed Method for Circuit Placement. Tony Chan 1 , Jason Cong 2 , Kenton Sze 1 1 UCLA Mathematics Department 2 UCLA Computer Science Department. This work is partially supported by SRC, NSF, and ONR. Outline. A Brief History of mPL

406 views • 25 slides

Placement and Coordinated Tuning of Control Devices for Capacity and Security Enhancement Using Genetic Algorithms and O

460 views • 24 slides

CSC2535: Advanced Machine Learning Lecture 11b Adaptation at multiple time-scales

CSC2535: Advanced Machine Learning Lecture 11b Adaptation at multiple time-scales. Geoffrey Hinton. An overview of how biology solves search problems. Searching for good combinations can be very slow if its done in a naive way. Evolution has found many ways to speed up searches.

356 views • 22 slides

Using Constraint Programming to Assign Students to First-year Seminars

Using Constraint Programming to Assign Students to First-year Seminars. Xiang Yao ( yaox@dickinson.edu ) Advisor: Timothy Wahls (wahlst@dickinson.edu) Submitted in partial fulfillment of Honors Requirements for the Computer Science Major?Dickinson College, 2013 March 17, 2014.

289 views • 15 slides

WORKFLOWS IN CLOUD COMPUTING

WORKFLOWS IN CLOUD COMPUTING. CLOUD COMPUTING. Delivering applications or services in on-demand environment Hundreds of thousands of users / applications Systems should be fast, secure and available All services and associated data Intelligent infrastructure: Transparency Scalability

423 views • 13 slides

Introduction to multi-objective optimization

Introduction to multi-objective optimization. We often have more than one objective This means that design points are no longer arranged in strict hierarchy There are points that are clearly poorer than others because all objectives are worse

750 views • 11 slides

Linear Programming

Linear Programming . Old name for linear optimization Linear objective functions and constraints Optimum always at boundary of feasible domain First solution algorithm, Simplex algorithm developed by George Dantzig , 1947 What is a simplex (e.g. triangle, tetrahedron)?

305 views • 11 slides

Optimization formulation

Optimization formulation. Optimization methods help us find solutions to problems where we seek to find the best of something. This lecture is about how we formulate the problem mathematically.

215 views • 10 slides

Quadratic Forms and Objective functions with two or more variables

Quadratic Forms and Objective functions with two or more variables. Two Choice Variables. Quadratic Forms Let Then ------------- can be written as ----------------- Definiteness Positive definite if q is invariably positive (q > 0)

1.12k views • 10 slides

Sensing and Acquisition & MOOS

Sensing and Acquisition & MOOS. Arjuna Balasuriya Sensing and Acquisition Sub-System. Release 1: S&A Services. Instrument Management Service Activate & manage instrument, start/stop the inst. agent Data Acquisition Service

222 views • 10 slides

PCEP Extension for WSON Routing and Wavelength Assignment

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Design, Analysis and Multi-Objective Constrained Optimization of Multi-Winglets

Design, Analysis and Multi-Objective Constrained Optimization of Multi-Winglets. Simultaneous Objectives Design Winglets to: Reduce drag Increase lift-to-drag ratio. Optimization Response surface methodology with genetic algorithm chosen as the optimization method

260 views • 1 slides