Truss Design Optimization with Imprecise Load and Stress in Neutrosophic Environment

Truss Design and Convex Optimization

Design Optimization with Imprecise Random Variables

Design optimization is an important engineering design activity. Performing design optimization in the presence of uncertainty has been an active area of research. The approaches used require modeling the random variables using precise probability distributions or representing uncertain quantities as fuzzy sets. This work, however, considers problems in which the random variables are described ...

qfd planning with cost consideration in fuzzy environment

در عصر حاضر که رقابت بین سازمان ها بسیار گسترش یافته است، مطالعه و طرحریزی سیستم های تولیدی و خدماتی به منظور بهینه سازی عملکرد آنها اجتناب ناپذیر می باشد. بخش عمده ای از رقابت پذیری سازمان ها نتیجه رضایتمندی مشتریان آنها است. میزان موفقیت سازمان های امروزی به تلاش آنها در جهت شناسایی خواسته ها و نیازهای مشتریان و ارضای این نیازها بستگی دارد. از طرفی کوتاه کردن زمان ارائه محصول/خدمات به مشتریان...

Optimal Truss Design Using Ant Colony Optimization

The paper presents a methodology to arrive at optimal truss designs using Ant Colony Optimization (ACO) algorithms. Ant Colony Optimization is a population-based, artificial multi-agent, general-search technique for the solution of difficult combinatorial problems with its theoretical roots based on the behavior of real ant colonies and the collective trail-laying and trail-following of its mem...

Optimization under uncertainty with applications to design of truss structures

Many real-world engineering design problems are naturally cast in the form of optimization programs with uncertainty-contaminated data. In this context, a reliable design must be able to cope in some way with the presence of uncertainty. In this paper, we consider two standard philosophies for finding optimal solutions for uncertain convex optimization problems. In the first approach, classical...