Multi objective optimization using (172 résultats)

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Paperback or Softback. Etat : New. Multi-Objective Mission Route Planning Using Particle Swarm Optimization. Book.

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Paperback. Etat : Very Good. 1st ed. 2016. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

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paperback. Etat : As New.

Etat : good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.…

hardcover. Etat : Good. Name written on the title page. Used copy with some highlighting/notations.

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Paperback or Softback. Etat : New. Multi-Objective Optimization of Mixed-Variable: Stochastic Systems Using Single-Objective Formulations. Book.

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gebundene Ausgabe. Etat : Gut. 220 Seiten; Das Buch befindet sich in einem ordentlich erhaltenen Zustand. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 501.

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Taschenbuch. Etat : Neu. Neuware - The Mission Routing Problem (MRP) is the selection of a vehicle path starting at a point, going through enemy terrain defended by radar sites to get to the target(s) and returning to a safe destination (usually the starting point). The MRP is a three-dimensional, multi-objective path search with constraints such as fuel expenditure, time limits, multi-targets, and radar sites with different levels of risks. It can severely task all the resources (people, hardware, software) of the system trying to compute the possible routes. The nature of the problem can cause operational planning systems to take longer to generate a solution than the time available. Since time is critical in MRP, it is important that a solution is reached within a relatively short time. It is not worth generating the solution if it takes days to calculate since the information may become invalid during that time. Particle Swarm Optimization (PSO) is an Evolutionary Algorithm (EA) technique that tries to find optimal solutions to complex problems using particles that interact with each other. Both Particle Swarm Optimization (PSO) and the Ant System (AS) have been shown to provide good solutions to Traveling Salesman Problem (TSP). PSO_AS is a synthesis of PSO and Ant System (AS). PSO_AS is a new approach for solving the MRP, and it produces good solutions. This thesis presents a new algorithm (PSO_AS) that functions to find the optimal solution by exploring the MRP search space stochastically.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. …

hardcover. Etat : Very Good. Very minor shelf and perusal wear. Pages are well bound. Text appears clean and unmarked.

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Paperback. Etat : Brand New. 76 pages. 8.66x5.91x0.18 inches. In Stock.

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PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

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Hardcover. Etat : Very Good. 1st Edition. Bright, clean hardcover with clean pages.