کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
493597 722785 2014 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Derivative-based hybrid heuristics for continuous-time simulation optimization
ترجمه فارسی عنوان
هیبرید مبتنی بر مبادله برای بهینه سازی شبیه سازی مداوم
کلمات کلیدی
اهرم هیبرید، روش های بهینه سازی مبتنی بر مشتقات، معادلات جبری دیفرانسیل، زبان های مدل سازی، مدلیکا
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی

The topic of simulation–optimization has not been fundamentally tackled by many continuous-time modeling and simulation tools, yet. Common simulation-based optimization problems are usually coupled with standard optimization algorithms like any other simulation-free nonlinear optimization problems. While such couplings are usually based on many state-of-the-art software engineering concepts with a high-level user interface for flexible incorporation of simulation and optimization, the design of specialized optimization strategies targeting simulation-based objective functions is lacked within many simulation–optimization tools. In this work, new redefinition of Non Linear Programming (NLP) problems in the context of continuous-time simulation optimization is presented. Then, the modified optimization problems are efficiently tackled using derivative-based hybrid heuristics. In order to specify, illustrate and implement such heuristics, a new terminology is proposed. According to the proposed terminology, derivative-based hybrid strategies are implemented by hybridizing naive multistart derivative-based optimization methods with population-based metaheuristics. It is shown that the adoption of derivative-based optimization methods within hybrid optimization strategies significantly improves the solution quality of continuous-time simulation optimization problems.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Simulation Modelling Practice and Theory - Volume 46, August 2014, Pages 164–175
نویسندگان
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