Evolutionary Exploration of Search Spaces
نویسنده
چکیده
Exploration and exploitation are the two cornerstones of problem solving by search. Evolutionary Algorithms (EAs) are search algorithms that explore the search space by the genetic search operators , while exploitation is done by selection. During the history of EAs diierent operators have emerged, mimicing asexual and sexual reproduction in Nature. Here we give an overview of the variety of these operators, review results discussing the (dis)advantages of asexual and sexual mechanisms and touch on a new phenomenon: multi-parent reproduction.
منابع مشابه
Chapter 3 HIERARCHICAL SYNTHESIS OF EMBEDDED SYSTEMS USING EVOLUTIONARY ALGORITHMS A Multi-Objective Approach
In this chapter, we propose an approach for the synthesis of heterogenous embedded systems, including allocation and binding problems. For solving these in general NP-complete problems, Evolutionary Algorithms have been proven to provide good solutions for search spaces of moderate size. For realistic embedded system applications, however, two more challenges must be considered: a) the complexi...
متن کاملOn the "Explorative Power" of ES/EP-like Algorithms
This paper discusses the question how ES/EP-like algorithms perform the evolutionary search in real-valued N-dimensional parameter spaces. It will be shown that the sometimes invoked model of a perturbed gradient search does not seem to give an appropriate picture of the search process. Instead, the search behavior is described as the antagonism of exploitation and exploration, where exploitati...
متن کاملExploring the search space of quantum programs
Here we present a first study of search spaces and fitness landscapes in the context of the evolution of quantum programs. We consider small instances of the Deutsch-Jozsa problem as a starting point for the exploration of search spaces of quantum algorithms and analyze the structure of mutation landscapes using autocorrelation functions and information measures for characterizing their behavio...
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 کاملSolving Multi-objective Optimal Control Problems of chemical processes using Hybrid Evolutionary Algorithm
Evolutionary algorithms have been recognized to be suitable for extracting approximate solutions of multi-objective problems because of their capability to evolve a set of non-dominated solutions distributed along the Pareto frontier. This paper applies an evolutionary optimization scheme, inspired by Multi-objective Invasive Weed Optimization (MOIWO) and Non-dominated Sorting (NS) strategi...
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 1996