Recent advances in computational opt...
Fidanova, Stefka.

 

  • Recent advances in computational optimization[electronic resource] :results of the Workshop on Computational Optimization WCO 2013 /
  • 紀錄類型: 書目-語言資料,印刷品 : Monograph/item
    杜威分類號: 006.3
    書名/作者: Recent advances in computational optimization : results of the Workshop on Computational Optimization WCO 2013 // edited by Stefka Fidanova.
    其他作者: Fidanova, Stefka.
    出版者: Cham : : Springer International Publishing :, 2015.
    面頁冊數: x, 193 p. : : ill., digital ;; 24 cm.
    Contained By: Springer eBooks
    標題: Combinatorial optimization
    標題: Computational intelligence
    標題: Engineering.
    標題: Artificial intelligence.
    標題: Operations research.
    標題: Computational Intelligence.
    標題: Artificial Intelligence (incl. Robotics)
    標題: Operation Research/Decision Theory.
    ISBN: 9783319126319 (electronic bk.)
    ISBN: 9783319126302 (paper)
    內容註: From the Contents: Three-Stage Heuristic for the Capacitated Vehicle Routing Problem with Time Windows -- Fuzzy bicriteria optimization approach to distribution network design -- Constraint Propagation for the Dial-a-Ride Problem with Split Loads -- Multiple shooting SQP algorithm for optimal control of DAE systems with inconsistent initial conditions.
    摘要、提要註: Our everyday life is unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit. Many real world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization 2013. It presents recent advances in computational optimization. The volume includes important real life problems like parameter settings for controlling processes in bioreactor, resource constrained project scheduling, problems arising in transport services, error correcting codes, optimal system performance and energy consumption and so on. It shows how to develop algorithms for them based on new metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming and others.
    電子資源: http://dx.doi.org/10.1007/978-3-319-12631-9
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