结晶启发式模拟退火的通用性:在大量问题中的应用

Tiago G. Goto, Hossein Rostami Najafabadi, Guilherme C. Duran, E. K. Ueda, A. K. Sato, Thiago de C. Martins, R. Y. Takimoto, H. Gohari, A. Barari, M. Tsuzuki
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引用次数: 1

摘要

本章涉及工程优化问题的几个方面。工程师通常用数学模型来解决问题,并创建一个必须最小化的功能,比如成本、所需时间、浪费的材料等。最终,函数必须最大化。这个函数在文献中有不同的名称:目标函数、成本函数等。我们在本章中将其称为目标函数。这些问题的可能性很大,可以用不同的方式进行分类。首先,参数的值可以是连续的、离散的(整数)、循环的(角度)、间隔的和组合的。目标函数的结果可以是连续的、离散的(整数)或区间的。一类非常困难的问题具有连续参数和离散目标函数,这类目标函数具有非常弱的敏感性。本章展示了模拟退火的多功能性,表明它可以有不同的参数和目标函数的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Versatility of Simulated Annealing with Crystallization Heuristic: Its Application to a Great Assortment of Problems
This chapter is related to several aspects of optimization problems in engineering. Engineers usually mathematically model a problem and create a function that must be minimized, like cost, required time, wasted material, etc. Eventually, the function must be maximized. This function has different names in the literature: objective function, cost function, etc. We will refer to it in the chapter as objective function. There is a wide range of possibilities for the problems and they can be classified in different ways. At first, the values of the parameters can be continuous, discrete (integers), cyclic (angles), intervals, and combinatorial. The result of the objective function can be continuous, discrete (integers) or intervals. One very difficult class of problems have continuous parameters and discrete objective function, this type of objective function has very weak sensibility. This chapter shows the versatility of the simulated annealing showing that it can have different possibilities of parameters and objective functions.
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