On the Usefulness of the Evolution Strategies’ Self-Adaptation Mechanism to Handle Constraints in Global Optimization
نویسندگان
چکیده
In this paper, we argue that the original self-adaptation mechanism of the Evolution Strategies is useful by itself to handle constraints in global optimization. We show how using just three simple comparison criteria the simple Evolution Strategy can be led to the feasible region of the search space and find the global optimum solution (or a very good approximation of it). Different Evolution Strategies including and with or without correlated mutation were implemented. Such approaches have been tested using the well-known test suit of Michalewicz and Schnoenauer and four engineering problems. The results are discussed and some conclusions are drawn.
منابع مشابه
THE CMA EVOLUTION STRATEGY BASED SIZE OPTIMIZATION OF TRUSS STRUCTURES
Evolution Strategies (ES) are a class of Evolutionary Algorithms based on Gaussian mutation and deterministic selection. Gaussian mutation captures pair-wise dependencies between the variables through a covariance matrix. Covariance Matrix Adaptation (CMA) is a method to update this covariance matrix. In this paper, the CMA-ES, which has found many applications in solving continuous optimizatio...
متن کاملOptimization of the Prismatic Core Sandwich Panel under Buckling Load and Yield Stress Constraints using an Improved Constrained Differential Evolution Algorithm
In this study, weight optimization of the prismatic core sandwich panel under transverse and longitudinal loadings has been independently investigated. To solve the optimization problems corresponding to the mentioned loadings, a new Improved Constrained Differential Evolution (ICDE) algorithm based on the multi-objective constraint handling method is implemented. The constraints of the problem...
متن کاملDYNAMIC PERFORMANCE OPTIMIZATION OF TRUSS STRUCTURES BASED ON AN IMPROVED MULTI-OBJECTIVE GROUP SEARCH OPTIMIZER
This paper presents an improved multi-objective group search optimizer (IMGSO) that is based on Pareto theory that is designed to handle multi-objective optimization problems. The optimizer includes improvements in three areas: the transition-feasible region is used to address constraints, the Dealer’s Principle is used to construct the non-dominated set, and the producer is updated using a tab...
متن کاملUsing the Evolution Strategies' Self-adaptation Mechanism and Tournament Selection for Global Optimization
An approach based on a (μ+1)-ES and three simple tournament rules is proposed to solve global optimization problems. The proposed approach does not use a penalty function and does not require any extra parameters other than the original parameters of an evolution strategy. This approach is validated with respect to the state-of-the-art techniques in evolutionary constrained optimization using a...
متن کاملOptimization in Uncertain and Complex Dynamic Environments with Evolutionary Methods
In the real world, many of the optimization issues are dynamic, uncertain, and complex in which the objective function or constraints can be changed over time. Consequently, the optimum of these issues is changed nonlinearly. Therefore, the optimization algorithms not only should search the global optimum value in the space but also should follow the path of optimal change in dynamic environmen...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2003