Scalarizations for adaptively solving multi-objective optimization problems

نویسندگان

چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Hybrid MOEA/D-TS for Solving Multi-Objective Problems

In many real-world applications, various optimization problems with conflicting objectives are very common. In this paper we employ Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), a newly developed method, beside Tabu Search (TS) accompaniment to achieve a new manner for solving multi-objective optimization problems (MOPs) with two or three conflicting objectives. This i...

متن کامل

Differential Evolution Algorithm for Solving Multi-objective Optimization Problems

This paper presents a modified Differential Evolution (DE) algorithm called OCMODE for solving multi-objective optimization problems. First, the initialization phase is improved by using the opposition based learning. Further, a time varying scale factor F employing chaotic sequence is used which helps to get a well distributed Pareto front by the help of non dominated and crowding distance sor...

متن کامل

Using traceless genetic programming for solving multi-objective optimization problems

Traceless Genetic Programming (TGP) is a Genetic Programming (GP) variant that is used in the cases where the focus is rather the output of the program than the program itself. The main difference between TGP and other GP techniques is that TGP does not explicitly store the evolved computer programs. Two genetic operators are used in conjunction with TGP: crossover and insertion. In this paper ...

متن کامل

A variant of NSGA for solving Multi objective optimization problems

Predicting the yield of various aromatic plants with the help

متن کامل

A FAST FUZZY-TUNED MULTI-OBJECTIVE OPTIMIZATION FOR SIZING PROBLEMS

The most recent approaches of multi-objective optimization constitute application of meta-heuristic algorithms for which, parameter tuning is still a challenge. The present work hybridizes swarm intelligence with fuzzy operators to extend crisp values of the main control parameters into especial fuzzy sets that are constructed based on a number of prescribed facts. Such parameter-less particle ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Computational Optimization and Applications

سال: 2007

ISSN: 0926-6003,1573-2894

DOI: 10.1007/s10589-007-9155-4