Combining the cross-entropy algorithm and ∈-constraint method for multiobjective optimization
نویسندگان
چکیده
منابع مشابه
Constraint Method-Based Evolutionary Algorithm (CMEA) for Multiobjective Optimization
Evolutionary algorithms are becoming increasingly valuable in solving large-scale, realistic engineering multiobjective optimization (MO) problems, which typically require consideration of conflicting and competing design issues. The new procedure, Constraint Method-Based Evolutionary Algorithm (CMEA), presented in this paper is based upon underlying concepts in the constraint method described ...
متن کاملCylindrical Constraint Evolutionary Algorithm for Multiobjective Optimization
This paper introduces a new iterative evolutionary algorithm, which is able to provide an evenly distributed set of solutions in multiobjective context. The method is different from the other evolutionary algorithms in two perspectives. First, instead of density information incorporated to find a diverse set of solutions, a hypercylinder is introduced as a new constraint to the problem. Searchi...
متن کاملThe Cross-Entropy Method for Optimization
The cross-entropy method is a versatile heuristic tool for solving difficult estimation and optimization problems, based on Kullback–Leibler (or cross-entropy) minimization. As an optimization method it unifies many existing populationbased optimization heuristics. In this chapter we show how the cross-entropy method can be applied to a diverse range of combinatorial, continuous, and noisy opti...
متن کاملCross Entropy multiobjective optimization for water distribution systems design
[1] A methodology extending the Cross Entropy combinatorial optimization method originating from an adaptive algorithm for rare events simulation estimation, to multiobjective optimization of water distribution systems design is developed and demonstrated. The single objective optimal design problem of a water distribution system is commonly to find the water distribution system component chara...
متن کاملEvaluation of the Constraint Method-Based Multiobjective Evolutionary Algorithm (CMEA) for a Three-Objective Optimization Problem
This paper presents a systematic comparative study of CMEA (constraint method-based multiobjective evolutionary algorithm) with several other commonly reported mulitobjective evolutionary algorithms (MOEAs) in solving a three-objective optimization problem. The best estimate of the noninferior space was also obtained by solving this multiobjective (MO) problem using a binary linear programming ...
متن کاملذخیره 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: Moroccan Journal of Pure and Applied Analysis
سال: 2021
ISSN: 2351-8227
DOI: 10.2478/mjpaa-2021-0019